Analysis and Prediction of Covid-19 Cases in India¶

This project will help to make analysis and to do visualization of data for Covid-19 disease in India as well as among the world. Also it helps to predict the values for Confirmed and deceased patients in future. We have applied machine Learning Alggorithm to predict the values, and also make visualization for those values.¶

#Importing required libraries
import pandas as pd
import numpy as np
import seaborn as sns
import matplotlib.pyplot as plt
import plotly.express as px

#Importing Dataset
df = pd.read_csv('Daily_India_covid_19.csv')
df

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 116 entries, 0 to 115
Data columns (total 8 columns):
 #   Column           Non-Null Count  Dtype 
---  ------           --------------  ----- 
 0   Date             116 non-null    object
 1   Daily Confirmed  116 non-null    int64 
 2   Daily Deaths     116 non-null    int64 
 3   Daily Recovered  116 non-null    int64 
 4   Total Confirmed  116 non-null    int64 
 5   Total Deaths     116 non-null    int64 
 6   Total Recovered  116 non-null    int64 
 7   Total Active     116 non-null    int64 
dtypes: int64(7), object(1)
memory usage: 7.4+ KB

Data Cleaning and Blending¶

# Adding year to the Date column
df['Date'] = df['Date'] + '-2020'

pd.set_option('display.max_rows',500)

df

# Changing the datatype of Date from object to datetime
df['Date'] = pd.to_datetime(df['Date'])
df['Date']

0     2020-01-30
1     2020-01-31
2     2020-02-01
3     2020-02-02
4     2020-02-03
5     2020-02-04
6     2020-02-05
7     2020-02-06
8     2020-02-07
9     2020-02-08
10    2020-02-09
11    2020-02-10
12    2020-02-11
13    2020-02-12
14    2020-02-13
15    2020-02-14
16    2020-02-15
17    2020-02-16
18    2020-02-17
19    2020-02-18
20    2020-02-19
21    2020-02-20
22    2020-02-21
23    2020-02-22
24    2020-02-23
25    2020-02-24
26    2020-02-25
27    2020-02-26
28    2020-02-27
29    2020-02-28
30    2020-02-29
31    2020-03-01
32    2020-03-02
33    2020-03-03
34    2020-03-04
35    2020-03-05
36    2020-03-06
37    2020-03-07
38    2020-03-08
39    2020-03-09
40    2020-03-10
41    2020-03-11
42    2020-03-12
43    2020-03-13
44    2020-03-14
45    2020-03-15
46    2020-03-16
47    2020-03-17
48    2020-03-18
49    2020-03-19
50    2020-03-20
51    2020-03-21
52    2020-03-22
53    2020-03-23
54    2020-03-24
55    2020-03-25
56    2020-03-26
57    2020-03-27
58    2020-03-28
59    2020-03-29
60    2020-03-30
61    2020-03-31
62    2020-04-01
63    2020-04-02
64    2020-04-03
65    2020-04-04
66    2020-04-05
67    2020-04-06
68    2020-04-07
69    2020-04-08
70    2020-04-09
71    2020-04-10
72    2020-04-11
73    2020-04-12
74    2020-04-13
75    2020-04-14
76    2020-04-15
77    2020-04-16
78    2020-04-17
79    2020-04-18
80    2020-04-19
81    2020-04-20
82    2020-04-21
83    2020-04-22
84    2020-04-23
85    2020-04-24
86    2020-04-25
87    2020-04-26
88    2020-04-27
89    2020-04-28
90    2020-04-29
91    2020-04-30
92    2020-05-01
93    2020-05-02
94    2020-05-03
95    2020-05-04
96    2020-05-05
97    2020-05-06
98    2020-05-07
99    2020-05-08
100   2020-05-09
101   2020-05-10
102   2020-05-11
103   2020-05-12
104   2020-05-13
105   2020-05-14
106   2020-05-15
107   2020-05-16
108   2020-05-17
109   2020-05-18
110   2020-05-19
111   2020-05-20
112   2020-05-21
113   2020-05-22
114   2020-05-23
115   2020-05-24
Name: Date, dtype: datetime64[ns]

df

Data Visualization¶

fig = px.bar(df, x="Date", y="Total Confirmed", color="Total Confirmed",
                  hover_data=['Total Confirmed'],
                 color_discrete_sequence = px.colors.sequential.Plasma_r)
fig.update_layout(title_text='Trend of Daily Coronavirus Cases in India',
                  plot_bgcolor='rgb(275, 270, 273)',width=800, height=600)
fig.show()

import plotly.graph_objs as go
fig = go.Figure(data=[
go.Bar(name='Confirmed', x=df['Date'], y=df['Total Confirmed'],marker_color='#FF0000'),
go.Bar(name='Recovered', x=df['Date'], y=df['Total Recovered'],marker_color='#2fcc41')])
fig.update_layout(barmode='stack',width=1000, height=600)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(title_text='Number of people Confirmed and Recovered among them',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.update_layout(plot_bgcolor='rgb(275, 270, 273)',yaxis_title='Total_Confirmed',xaxis_title='Date')
fig.show()

import plotly.graph_objs as go
fig = go.Figure(data=[
go.Bar(name='Confirmed', x=df['Date'], y=df['Total Confirmed'],marker_color='#FF0000'),
go.Bar(name='Deaths', x=df['Date'], y=df['Total Deaths'],marker_color='Blue')])
fig.update_layout(barmode='stack',width=1000, height=600)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(title_text='Number of people Confirmed and Deceased among them',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.update_layout(plot_bgcolor='rgb(275, 270, 273)',yaxis_title='Total_Deaths',xaxis_title='Date')
fig.show()

# Splitting of the Date column
def add_features(df):
    df['Year'] = df['Date'].dt.year
    df['Month'] = df['Date'].dt.month
    df['Week'] = df['Date'].dt.week
    df['Day'] = df['Date'].dt.day

add_features(df)

df.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 116 entries, 0 to 115
Data columns (total 12 columns):
 #   Column           Non-Null Count  Dtype         
---  ------           --------------  -----         
 0   Date             116 non-null    datetime64[ns]
 1   Daily Confirmed  116 non-null    int64         
 2   Daily Deaths     116 non-null    int64         
 3   Daily Recovered  116 non-null    int64         
 4   Total Confirmed  116 non-null    int64         
 5   Total Deaths     116 non-null    int64         
 6   Total Recovered  116 non-null    int64         
 7   Total Active     116 non-null    int64         
 8   Year             116 non-null    int64         
 9   Month            116 non-null    int64         
 10  Week             116 non-null    int64         
 11  Day              116 non-null    int64         
dtypes: datetime64[ns](1), int64(11)
memory usage: 11.0 KB

df

# Slicing of the data
data = df[62:]
data

d = data[['Day']]
w = data[['Week']]
m = data[['Month']]
y = data[['Total Confirmed']]

plt.plot(d,y, label=r'$Confirmed Cases$', color='red')
plt.gca().update(dict(title='Day vs Confirmed_Cases', xlabel='Day', ylabel='Total Confirmed'))
plt.legend()
plt.show()

plt.plot(w,y, label=r'$Confirmed Cases$', color='green')
plt.gca().update(dict(title='Week vs Confirmed_Cases', xlabel='Week', ylabel='Total Confirmed'))
plt.legend()
plt.show()

plt.plot(m,y, label=r'$Confirmed Cases$', color='blue')
plt.gca().update(dict(title='Month vs Confirmed_Cases', xlabel='Month', ylabel='Total Confirmed'))
plt.legend()
plt.show()

#Importing train test split model for Confirmed cases per Week
from sklearn.model_selection import train_test_split
x_train, x_test, y_train, y_test = train_test_split(w, y, train_size= 0.9)

x_train

y_train

#Importing and Fitting Machine Learning Algorithm 
from sklearn.linear_model import LinearRegression
model = LinearRegression()
model.fit(x_train,y_train)

LinearRegression()

#Predicting Values
model.predict([[24],[27],[30],[35],[40]])

array([[148204.11342672],
       [197171.73385719],
       [246139.35428767],
       [327752.05500512],
       [409364.75572258]])

predict = model.predict(x_train)
predict

array([[ 66591.41270926],
       [ 50268.87256577],
       [ 50268.87256577],
       [ 33946.33242228],
       [ 99236.49299624],
       [  1301.25213529],
       [ 99236.49299624],
       [ 17623.79227878],
       [ 66591.41270926],
       [ 66591.41270926],
       [-15021.2880082 ],
       [ 17623.79227878],
       [ 50268.87256577],
       [ 33946.33242228],
       [ 82913.95285275],
       [ 33946.33242228],
       [ 17623.79227878],
       [ 50268.87256577],
       [  1301.25213529],
       [ 50268.87256577],
       [ 99236.49299624],
       [ 17623.79227878],
       [ 99236.49299624],
       [ 82913.95285275],
       [ 82913.95285275],
       [ 99236.49299624],
       [  1301.25213529],
       [ 50268.87256577],
       [ 50268.87256577],
       [ 66591.41270926],
       [ 17623.79227878],
       [ 17623.79227878],
       [ 82913.95285275],
       [ 33946.33242228],
       [ 82913.95285275],
       [ 82913.95285275],
       [-15021.2880082 ],
       [  1301.25213529],
       [ 17623.79227878],
       [-15021.2880082 ],
       [ 82913.95285275],
       [  1301.25213529],
       [ 33946.33242228],
       [-15021.2880082 ],
       [  1301.25213529],
       [ 33946.33242228],
       [-15021.2880082 ],
       [ 99236.49299624]])

#Comparing Predicted and Actual Values

plt.scatter(x_train, predict, color='red', marker='*', label=r'$Predicted Values$')
plt.scatter(x_train, y_train, color='green', marker='o', label=r'$Actual Values$')
plt.gca().update(dict(title='Predicted_values vs Actual_Values', xlabel='Day', ylabel='Total Confirmed'))
plt.legend()
plt.show()

#Accuracy of the Model
model.score(x_train,y_train)*100

87.3480748721295

Importing Prophet Model¶

#Importing Prophet
from fbprophet import Prophet

test = data[['Date', 'Total Confirmed']]

test

# Changing the column names
test.columns = ['ds','y']

test.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 54 entries, 62 to 115
Data columns (total 2 columns):
 #   Column  Non-Null Count  Dtype         
---  ------  --------------  -----         
 0   ds      54 non-null     datetime64[ns]
 1   y       54 non-null     int64         
dtypes: datetime64[ns](1), int64(1)
memory usage: 996.0 bytes

#Fitting Prophet model
m = Prophet()
m.fit(test)

INFO:fbprophet:Disabling yearly seasonality. Run prophet with yearly_seasonality=True to override this.
INFO:fbprophet:Disabling daily seasonality. Run prophet with daily_seasonality=True to override this.

<fbprophet.forecaster.Prophet at 0xf890a08>

# Creating future values
future = m.make_future_dataframe(periods=90,freq='D')
future

len(test)

54

len(future)

144

#Predicting Future Values
forecast = m.predict(future)
forecast

forecast.columns

Index(['ds', 'trend', 'yhat_lower', 'yhat_upper', 'trend_lower', 'trend_upper',
       'additive_terms', 'additive_terms_lower', 'additive_terms_upper',
       'weekly', 'weekly_lower', 'weekly_upper', 'multiplicative_terms',
       'multiplicative_terms_lower', 'multiplicative_terms_upper', 'yhat'],
      dtype='object')

# Predicted Values for future
forecast[['ds', 'trend', 'yhat_lower', 'yhat_upper', 'yhat']]

# Plotting forecast graph between ds and y
m.plot(forecast);

# Plotting forecast graph between ds and yhat
forecast.plot(x='ds', y='yhat', color='red');

# Plotting graphs "ds vs trend" and "Day of week vs weekly values" 
m.plot_components(forecast);

Analysis of Covid-19 for different States in India¶

df1 = pd.read_csv('Total_India_covid-19.csv')
df1

df1.info()

<class 'pandas.core.frame.DataFrame'>
RangeIndex: 37 entries, 0 to 36
Data columns (total 9 columns):
 #   Column        Non-Null Count  Dtype  
---  ------        --------------  -----  
 0   State         37 non-null     object 
 1   Statecode     37 non-null     object 
 2   Confirmed     37 non-null     int64  
 3   Active        37 non-null     int64  
 4   Recovered     37 non-null     int64  
 5   Deaths        37 non-null     int64  
 6   Last Updated  37 non-null     object 
 7   Latitude      36 non-null     float64
 8   Longitude     36 non-null     float64
dtypes: float64(2), int64(4), object(3)
memory usage: 2.7+ KB

import plotly.graph_objs as go
fig = go.Figure(data=[
go.Bar(name='Confirmed', x=df1['Statecode'], y=df1['Confirmed'],marker_color='#FF0000'),
go.Bar(name='Recovered', x=df1['Statecode'], y=df1['Recovered'],marker_color='#2fcc41')])
fig.update_layout(barmode='stack',width=1000, height=600)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(title_text='Statewise Number of people Confirmed and Recovered among them',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.update_layout(plot_bgcolor='rgb(275, 270, 273)',yaxis_title='Total_Confirmed',xaxis_title='State')
fig.show()

import plotly.graph_objs as go
fig = go.Figure(data=[
go.Bar(name='Confirmed', x=df1['Statecode'], y=df1['Confirmed'],marker_color='#FF0000'),
go.Bar(name='Deaths', x=df1['Statecode'], y=df1['Deaths'],marker_color='Blue')])
fig.update_layout(barmode='stack',width=1000, height=600)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(title_text='Statewise Number of people Confirmed and Deceased among them',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.update_layout(plot_bgcolor='rgb(275, 270, 273)',yaxis_title='Total_Confirmed',xaxis_title='State')
fig.show()

px.pie(df1, values='Confirmed', names='State', title='Statewise Number of people Confirmed')

fig = go.Figure(data=[go.Pie(labels=df1.State, values=df1.Deaths, hole=.3)])
fig.update_layout(title_text='Statewise Number of people Deceased',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.show()

Analysis of Covid-19 among world¶

df2 = pd.read_csv('Total_World_covid-19.csv')
df2

import plotly.graph_objs as go
fig = go.Figure(data=[
go.Bar(name='Confirmed', x=df2['Country'], y=df2['Confirmed'],marker_color='#FF0000'),
go.Bar(name='Recovered', x=df2['Country'], y=df2['Recovered'],marker_color='#2fcc41')])
fig.update_layout(barmode='stack',width=3000, height=600)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(title_text='Countrywise Number of people Confirmed and Recovered among them',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.update_layout(plot_bgcolor='rgb(275, 270, 273)',yaxis_title='Total_Confirmed',xaxis_title='Country')
fig.show()

import plotly.graph_objs as go
fig = go.Figure(data=[
go.Bar(name='Confirmed', x=df2['Country'], y=df2['Confirmed'],marker_color='#FF0000'),
go.Bar(name='Deceased', x=df2['Country'], y=df2['Deaths'],marker_color='blue')])
fig.update_layout(barmode='stack',width=3000, height=600)
fig.update_traces(textposition='inside')
fig.update_layout(uniformtext_minsize=8, uniformtext_mode='hide')
fig.update_layout(title_text='Countrywise Number of people Confirmed and Deceased among them',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.update_layout(plot_bgcolor='rgb(275, 270, 273)',yaxis_title='Total_Confirmed',xaxis_title='Country')
fig.show()

px.pie(df2, values='Confirmed', names='Country', color='Population', title='Countrywise Number of people Confirmed')

fig = go.Figure(data=[go.Pie(labels=df2.Country, values=df2.Deaths, hole=.3)])
fig.update_layout(title_text='Countrywise Number of people Deceased',
                  plot_bgcolor='rgb(275, 270, 273)')
fig.show()

Result: In this project we have analyze the data for Covid-19. Also we have applied Machine Learning Algorithm as well as Prophet model to predict the future data. We have done data visualization of present as well as future data. our accuracy of model prediction is 87.98%.¶

	Date	Daily Confirmed	Daily Deaths	Daily Recovered	Total Confirmed	Total Deaths	Total Recovered	Total Active
0	30-Jan	1	0	0	1	0	0	1
1	31-Jan	0	0	0	1	0	0	1
2	01-Feb	0	0	0	1	0	0	1
3	02-Feb	1	0	0	2	0	0	2
4	03-Feb	1	0	0	3	0	0	3
...	...	...	...	...	...	...	...	...
111	20-May	5720	134	3113	112200	3435	45422	63343
112	21-May	6023	148	3131	118223	3583	48553	66087
113	22-May	6536	142	3280	124759	3725	51833	69201
114	23-May	6665	142	2576	131422	3867	54409	73146
115	24-May	7111	156	3283	138535	4023	57692	76820

	Date	Daily Confirmed	Daily Deaths	Daily Recovered	Total Confirmed	Total Deaths	Total Recovered	Total Active
0	30-Jan-2020	1	0	0	1	0	0	1
1	31-Jan-2020	0	0	0	1	0	0	1
2	01-Feb-2020	0	0	0	1	0	0	1
3	02-Feb-2020	1	0	0	2	0	0	2
4	03-Feb-2020	1	0	0	3	0	0	3
5	04-Feb-2020	0	0	0	3	0	0	3
6	05-Feb-2020	0	0	0	3	0	0	3
7	06-Feb-2020	0	0	0	3	0	0	3
8	07-Feb-2020	0	0	0	3	0	0	3
9	08-Feb-2020	0	0	0	3	0	0	3
10	09-Feb-2020	0	0	0	3	0	0	3
11	10-Feb-2020	0	0	0	3	0	0	3
12	11-Feb-2020	0	0	0	3	0	0	3
13	12-Feb-2020	0	0	0	3	0	0	3
14	13-Feb-2020	0	0	1	3	0	1	2
15	14-Feb-2020	0	0	0	3	0	1	2
16	15-Feb-2020	0	0	0	3	0	1	2
17	16-Feb-2020	0	0	1	3	0	2	1
18	17-Feb-2020	0	0	0	3	0	2	1
19	18-Feb-2020	0	0	0	3	0	2	1
20	19-Feb-2020	0	0	0	3	0	2	1
21	20-Feb-2020	0	0	1	3	0	3	0
22	21-Feb-2020	0	0	0	3	0	3	0
23	22-Feb-2020	0	0	0	3	0	3	0
24	23-Feb-2020	0	0	0	3	0	3	0
25	24-Feb-2020	0	0	0	3	0	3	0
26	25-Feb-2020	0	0	0	3	0	3	0
27	26-Feb-2020	0	0	0	3	0	3	0
28	27-Feb-2020	0	0	0	3	0	3	0
29	28-Feb-2020	0	0	0	3	0	3	0
30	29-Feb-2020	0	0	0	3	0	3	0
31	01-Mar-2020	0	0	0	3	0	3	0
32	02-Mar-2020	2	0	0	5	0	3	2
33	03-Mar-2020	1	0	0	6	0	3	3
34	04-Mar-2020	22	0	0	28	0	3	25
35	05-Mar-2020	2	0	0	30	0	3	27
36	06-Mar-2020	1	0	0	31	0	3	28
37	07-Mar-2020	3	0	0	34	0	3	31
38	08-Mar-2020	5	0	0	39	0	3	36
39	09-Mar-2020	9	0	0	48	0	3	45
40	10-Mar-2020	15	0	1	63	0	4	59
41	11-Mar-2020	8	0	0	71	0	4	67
42	12-Mar-2020	10	1	0	81	1	4	76
43	13-Mar-2020	10	0	6	91	1	10	80
44	14-Mar-2020	11	1	0	102	2	10	90
45	15-Mar-2020	10	0	3	112	2	13	97
46	16-Mar-2020	14	0	1	126	2	14	110
47	17-Mar-2020	20	1	1	146	3	15	128
48	18-Mar-2020	25	0	0	171	3	15	153
49	19-Mar-2020	27	1	5	198	4	20	174
50	20-Mar-2020	58	0	3	256	4	23	229
51	21-Mar-2020	78	0	0	334	4	23	307
52	22-Mar-2020	69	3	0	403	7	23	373
53	23-Mar-2020	94	2	2	497	9	25	463
54	24-Mar-2020	74	1	15	571	10	40	521
55	25-Mar-2020	86	1	3	657	11	43	603
56	26-Mar-2020	73	5	7	730	16	50	664
57	27-Mar-2020	153	3	25	883	19	75	789
58	28-Mar-2020	136	5	10	1019	24	85	910
59	29-Mar-2020	120	3	17	1139	27	102	1010
60	30-Mar-2020	187	14	35	1326	41	137	1148
61	31-Mar-2020	309	6	13	1635	47	150	1438
62	01-Apr-2020	424	6	19	2059	53	169	1837
63	02-Apr-2020	486	16	22	2545	69	191	2285
64	03-Apr-2020	560	14	39	3105	83	230	2792
65	04-Apr-2020	579	13	56	3684	96	286	3302
66	05-Apr-2020	609	22	43	4293	118	329	3846
67	06-Apr-2020	484	16	65	4777	134	394	4249
68	07-Apr-2020	573	27	75	5350	161	469	4720
69	08-Apr-2020	565	20	96	5915	181	565	5169
70	09-Apr-2020	813	46	70	6728	227	635	5866
71	10-Apr-2020	871	22	151	7599	249	786	6564
72	11-Apr-2020	854	41	186	8453	290	972	7191
73	12-Apr-2020	758	42	114	9211	332	1086	7793
74	13-Apr-2020	1243	27	112	10454	359	1198	8897
75	14-Apr-2020	1031	37	167	11485	396	1365	9724
76	15-Apr-2020	886	27	144	12371	423	1509	10439
77	16-Apr-2020	1061	26	258	13432	449	1767	11216
78	17-Apr-2020	922	38	273	14354	487	2040	11827
79	18-Apr-2020	1371	35	426	15725	522	2466	12737
80	19-Apr-2020	1580	38	388	17305	560	2854	13891
81	20-Apr-2020	1239	33	419	18544	593	3273	14678
82	21-Apr-2020	1537	53	703	20081	646	3976	15459
83	22-Apr-2020	1292	36	394	21373	682	4370	16321
84	23-Apr-2020	1667	40	642	23040	722	5012	17306
85	24-Apr-2020	1408	59	484	24448	781	5496	18171
86	25-Apr-2020	1835	44	442	26283	825	5938	19520
87	26-Apr-2020	1607	56	585	27890	881	6523	20486
88	27-Apr-2020	1568	58	580	29458	939	7103	21416
89	28-Apr-2020	1902	69	636	31360	1008	7739	22613
90	29-Apr-2020	1705	71	690	33065	1079	8429	23557
91	30-Apr-2020	1801	75	630	34866	1154	9059	24653
92	01-May-2020	2396	77	962	37262	1231	10021	26010
93	02-May-2020	2564	92	831	39826	1323	10852	27651
94	03-May-2020	2952	140	911	42778	1463	11763	29552
95	04-May-2020	3656	103	1082	46434	1566	12845	32023
96	05-May-2020	2971	128	1295	49405	1694	14140	33571
97	06-May-2020	3602	91	1161	53007	1785	15301	35921
98	07-May-2020	3344	104	1475	56351	1889	16776	37686
99	08-May-2020	3339	97	1111	59690	1986	17887	39817
100	09-May-2020	3175	115	1414	62865	2101	19301	41463
101	10-May-2020	4311	112	1669	67176	2213	20970	43993
102	11-May-2020	3592	81	1579	70768	2294	22549	45925
103	12-May-2020	3562	120	1905	74330	2414	24454	47462
104	13-May-2020	3726	137	1963	78056	2551	26417	49088
105	14-May-2020	3991	97	1594	82047	2648	28011	51388
106	15-May-2020	3808	104	2234	85855	2752	30245	52858
107	16-May-2020	4794	120	4012	90649	2872	34257	53520
108	17-May-2020	5049	152	2538	95698	3024	36795	55879
109	18-May-2020	4628	131	2482	100326	3155	39277	57894
110	19-May-2020	6154	146	3032	106480	3301	42309	60870
111	20-May-2020	5720	134	3113	112200	3435	45422	63343
112	21-May-2020	6023	148	3131	118223	3583	48553	66087
113	22-May-2020	6536	142	3280	124759	3725	51833	69201
114	23-May-2020	6665	142	2576	131422	3867	54409	73146
115	24-May-2020	7111	156	3283	138535	4023	57692	76820

	ds	trend	yhat_lower	yhat_upper	trend_lower	trend_upper	additive_terms	additive_terms_lower	additive_terms_upper	weekly	weekly_lower	weekly_upper	yhat
0	2020-04-01	1562.478044	440.134391	2705.934471	1562.478044	1562.478044	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	1597.808197
1	2020-04-02	2237.589341	1034.642193	3424.697178	2237.589341	2237.589341	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	2215.132558
2	2020-04-03	2912.700637	1593.587836	3999.316225	2912.700637	2912.700637	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	2850.321864
3	2020-04-04	3587.811933	2448.872845	4824.079486	3587.811933	3587.811933	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	3649.634237
4	2020-04-05	4262.923246	3282.597276	5717.911227	4262.923246	4262.923246	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	4582.161725
5	2020-04-06	4938.034559	3610.116626	5875.782594	4938.034559	4938.034559	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	4715.881648
6	2020-04-07	5613.557237	4332.059007	6617.467544	5613.557237	5613.557237	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	5504.154769
7	2020-04-08	6289.079916	5121.991510	7475.741192	6289.079916	6289.079916	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	6324.410068
8	2020-04-09	6964.888527	5764.247428	8058.687867	6964.888527	6964.888527	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	6942.431744
9	2020-04-10	7641.105899	6419.106369	8709.616752	7641.105899	7641.105899	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	7578.727125
10	2020-04-11	8317.323271	7271.478616	9472.300589	8317.323271	8317.323271	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	8379.145575
11	2020-04-12	9350.423222	8523.346750	10775.219594	9350.423222	9350.423222	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	9669.661701
12	2020-04-13	10383.523173	9059.127535	11271.647286	10383.523173	10383.523173	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	10161.370262
13	2020-04-14	11420.715229	10128.493831	12404.474412	11420.715229	11420.715229	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	11311.312761
14	2020-04-15	12459.491372	11376.004560	13725.012122	12459.491372	12459.491372	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	12494.821524
15	2020-04-16	13498.267514	12290.895406	14639.515867	13498.267514	13498.267514	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	13475.810731
16	2020-04-17	14539.482482	13298.366420	15615.946024	14539.482482	14539.482482	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	14477.103708
17	2020-04-18	15580.697450	14511.271692	16841.877709	15580.697450	15580.697450	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	15642.519754
18	2020-04-19	17074.725041	16201.063865	18472.646654	17074.725041	17074.725041	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	17393.963521
19	2020-04-20	18569.805190	17225.317921	19569.585432	18569.805190	18569.805190	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	18347.652279
20	2020-04-21	20064.885339	18732.222164	21123.151314	20064.885339	20064.885339	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	19955.482870
21	2020-04-22	21560.224801	20426.871059	22664.249893	21560.224801	21560.224801	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	21595.554953
22	2020-04-23	23055.564263	21888.210244	24201.274641	23055.564263	23055.564263	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	23033.107481
23	2020-04-24	24552.411091	23408.020268	25720.421802	24552.411091	24552.411091	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	24490.032317
24	2020-04-25	26049.257918	24896.855584	27295.947092	26049.257918	26049.257918	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	26111.080222
25	2020-04-26	27814.690142	26998.889314	29301.840256	27814.690142	27814.690142	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	28133.928621
26	2020-04-27	29580.695641	28205.591442	30551.669636	29580.695641	29580.695641	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	29358.542730
27	2020-04-28	31346.701140	30067.097644	32412.997284	31346.701140	31346.701140	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	31237.298672
28	2020-04-29	33113.325235	32019.270242	34302.767216	33113.325235	33113.325235	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	33148.655388
29	2020-04-30	34879.949331	33742.390857	36025.080427	34879.949331	34879.949331	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	34857.492548
30	2020-05-01	37153.300539	35923.091799	38272.404192	37153.300539	37153.300539	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	37090.921765
31	2020-05-02	40108.669027	39107.265683	41441.144751	40108.669027	40108.669027	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	40170.491331
32	2020-05-03	43064.037515	42317.075542	44578.058716	43064.037515	43064.037515	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	43383.275994
33	2020-05-04	46376.153248	44962.868596	47353.848413	46376.153248	46376.153248	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	46154.000337
34	2020-05-05	49688.268980	48444.117785	50649.532012	49688.268980	49688.268980	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	49578.866512
35	2020-05-06	53001.237170	51820.343181	54171.963036	53001.237170	53001.237170	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	53036.567322
36	2020-05-07	56314.270957	55234.699638	57402.993430	56314.270957	56314.270957	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	56291.814175
37	2020-05-08	59627.304745	58411.461735	60700.770653	59627.304745	59627.304745	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	59564.925971
38	2020-05-09	62940.338565	61778.952642	64102.832707	62940.338565	62940.338565	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	63002.160870
39	2020-05-10	66253.372386	65374.837665	67686.540616	66253.372386	66253.372386	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	66572.610865
40	2020-05-11	69566.406218	68197.174461	70472.763237	69566.406218	69566.406218	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	69344.253307
41	2020-05-12	72879.440071	71608.416637	73905.171848	72879.440071	72879.440071	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	72770.037603
42	2020-05-13	76192.473924	75076.169259	77362.875862	76192.473924	76192.473924	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	76227.804076
43	2020-05-14	81534.271915	80327.909869	82613.086202	81534.271915	81534.271915	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	81511.815132
44	2020-05-15	86876.069906	85765.343004	87843.251095	86876.069906	86876.069906	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	86813.691132
45	2020-05-16	92217.867896	91141.214712	93381.722915	92217.867896	92217.867896	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	92279.690201
46	2020-05-17	97559.665887	96698.804978	99057.519539	97559.665887	97559.665887	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	97878.904367
47	2020-05-18	102901.463878	101467.879787	103771.762262	102901.463878	102901.463878	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	102679.310967
48	2020-05-19	108243.261869	107012.301142	109269.511667	108243.261869	108243.261869	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	108133.859401
49	2020-05-20	113585.059859	112575.776950	114805.285674	113585.059859	113585.059859	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	113620.390012
50	2020-05-21	118926.857850	117676.952834	120088.135413	118926.857850	118926.857850	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	118904.401067
51	2020-05-22	124268.655841	123058.293191	125361.670745	124268.655841	124268.655841	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	124206.277067
52	2020-05-23	129610.453832	128474.002813	130878.098212	129610.453832	129610.453832	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	129672.276136
53	2020-05-24	134952.251823	134040.065671	136373.079329	134952.251823	134952.251823	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	135271.490302
54	2020-05-25	140294.049813	138834.800789	141206.219064	140246.617880	140355.686853	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	140071.896902
55	2020-05-26	145635.847804	144332.255357	146784.975278	145361.977750	145912.825635	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	145526.445336
56	2020-05-27	150977.645795	149695.997101	152300.431377	150386.604543	151535.012198	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	151012.975947
57	2020-05-28	156319.443786	154726.107375	157759.669729	155309.268585	157192.632488	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	156296.987003
58	2020-05-29	161661.241776	159798.336317	163415.065260	160275.481514	162827.998647	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	161598.863002
59	2020-05-30	167003.039767	164900.636692	168938.399581	165067.991393	168642.859124	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	167064.862071
60	2020-05-31	172344.837758	169954.023235	175097.897972	169953.953400	174511.663126	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	172664.076237
61	2020-06-01	177686.635749	174364.053397	180249.856038	174635.389920	180328.532486	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	177464.482838
62	2020-06-02	183028.433739	179136.459892	186381.581877	179502.713043	186272.233983	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	182919.031271
63	2020-06-03	188370.231730	184105.292071	192265.986806	184162.846057	192176.325211	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	188405.561882
64	2020-06-04	193712.029721	188742.230797	198289.932625	188890.110112	198140.656362	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	193689.572938
65	2020-06-05	199053.827712	193359.065854	204065.962930	193603.333139	204142.911022	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	198991.448938
66	2020-06-06	204395.625702	198191.660663	210352.396191	198269.640382	210250.401631	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	204457.448007
67	2020-06-07	209737.423693	203112.309328	216791.735624	203053.239198	216315.769992	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	210056.662172
68	2020-06-08	215079.221684	207313.820199	222245.863465	207596.027713	222504.477283	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	214857.068773
69	2020-06-09	220421.019675	211676.990344	228580.825435	212120.734318	228669.230359	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	220311.617207
70	2020-06-10	225762.817665	216772.320285	235021.840862	216772.710110	234563.175776	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	225798.147818
71	2020-06-11	231104.615656	221193.811300	240941.529820	221241.899946	241033.372518	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	231082.158873
72	2020-06-12	236446.413647	225396.034728	247282.971939	225644.989191	247406.218765	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	236384.034873
73	2020-06-13	241788.211638	230001.430264	253894.376628	230055.259072	253689.279462	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	241850.033942
74	2020-06-14	247130.009629	234908.101070	260550.491259	234514.806953	259890.644050	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	247449.248108
75	2020-06-15	252471.807619	238774.520813	266144.206152	238962.665923	266219.777054	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	252249.654708
76	2020-06-16	257813.605610	243083.598379	272263.139253	243227.200999	272383.963933	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	257704.203142
77	2020-06-17	263155.403601	247950.194877	278853.422423	247601.661160	278528.451549	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	263190.733753
78	2020-06-18	268497.201592	251929.981926	284658.199534	251793.150710	284884.084393	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	268474.744809
79	2020-06-19	273838.999582	256068.388171	291051.162361	256044.503000	291192.321973	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	273776.620808
80	2020-06-20	279180.797573	260255.471779	298124.645436	260388.040904	297809.455800	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	279242.619877
81	2020-06-21	284522.595564	264949.933831	304250.664411	264557.951871	304276.358791	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	284841.834043
82	2020-06-22	289864.393555	268200.598124	310034.725701	268749.069251	310741.241214	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	289642.240644
83	2020-06-23	295206.191545	273114.052177	316149.014826	273042.916523	317113.730300	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	295096.789077
84	2020-06-24	300547.989536	277393.710867	323248.677369	277242.648368	323303.189586	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	300583.319688
85	2020-06-25	305889.787527	281775.432075	329728.601047	281583.962481	330065.770041	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	305867.330744
86	2020-06-26	311231.585518	285845.406937	336141.774449	285717.752783	336133.782676	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	311169.206744
87	2020-06-27	316573.383508	290196.368269	342729.917248	290062.242405	342576.503023	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	316635.205813
88	2020-06-28	321915.181499	295226.082647	349181.491201	294406.612871	348972.631973	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	322234.419978
89	2020-06-29	327256.979490	297938.378231	354818.488081	298371.620335	355379.699342	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	327034.826579
90	2020-06-30	332598.777481	302665.794443	362216.539980	302299.217580	361858.773432	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	332489.375013
91	2020-07-01	337940.575471	307154.440032	368533.463540	306400.156119	368547.352539	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	337975.905624
92	2020-07-02	343282.373462	310469.244568	374779.996800	310427.666772	375452.667573	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	343259.916679
93	2020-07-03	348624.171453	314390.389501	381729.826374	314576.554238	381998.633448	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	348561.792679
94	2020-07-04	353965.969444	318007.920114	388725.138101	318577.880230	388152.337967	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	354027.791748
95	2020-07-05	359307.767434	322730.421822	395716.021872	322794.304675	395200.080823	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	359627.005914
96	2020-07-06	364649.565425	325908.688693	401849.106220	326865.855190	401918.515217	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	364427.412514
97	2020-07-07	369991.363416	330321.348559	408884.701987	330884.440726	408718.784134	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	369881.960948
98	2020-07-08	375333.161407	334391.498173	415319.993385	335023.535687	415555.776330	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	375368.491559
99	2020-07-09	380674.959398	338575.623560	422458.895341	339331.170776	422610.711250	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	380652.502615
100	2020-07-10	386016.757388	342806.631575	429505.407082	343400.930711	429573.645751	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	385954.378614
101	2020-07-11	391358.555379	347592.406139	436903.793843	347402.658922	436299.374999	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	391420.377683
102	2020-07-12	396700.353370	350873.159068	443262.863755	351005.562397	443396.922787	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	397019.591849
103	2020-07-13	402042.151361	354110.369105	450218.733937	354659.952963	450159.019312	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	401819.998450
104	2020-07-14	407383.949351	358715.241542	456294.525478	358672.149531	456604.994759	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	407274.546883
105	2020-07-15	412725.747342	362924.354884	463762.548022	362979.407283	463637.941211	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	412761.077494
106	2020-07-16	418067.545333	367125.791351	470003.918844	367186.018448	470644.502688	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	418045.088550
107	2020-07-17	423409.343324	371256.560499	477219.652589	371199.052161	477100.979047	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	423346.964550
108	2020-07-18	428751.141314	374521.132797	483957.415499	374588.753097	483341.066164	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	428812.963619
109	2020-07-19	434092.939305	378124.567718	491051.135208	378444.512768	490426.783035	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	434412.177784
110	2020-07-20	439434.737296	381608.662638	497575.119169	381782.122414	497528.827532	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	439212.584385
111	2020-07-21	444776.535287	385517.915238	504785.693662	385584.299858	504497.052243	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	444667.132819
112	2020-07-22	450118.333277	388871.804832	511748.572767	389405.768689	511259.541004	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	450153.663430
113	2020-07-23	455460.131268	393345.143974	518362.270241	393234.778136	518567.208320	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	455437.674485
114	2020-07-24	460801.929259	396309.083492	526530.140740	396639.889702	525915.346000	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	460739.550485
115	2020-07-25	466143.727250	400090.593839	533052.499856	399645.779707	533222.088606	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	466205.549554
116	2020-07-26	471485.525240	404242.216051	541117.739535	403179.982170	540468.937714	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	471804.763720
117	2020-07-27	476827.323231	406251.310414	547263.381340	405785.787022	547858.322647	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	476605.170320
118	2020-07-28	482169.121222	408320.535371	554624.248012	408810.846803	555000.715053	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	482059.718754
119	2020-07-29	487510.919213	412760.648468	561330.471883	413018.700029	561520.610515	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	487546.249365
120	2020-07-30	492852.717204	415654.332870	568785.045544	416606.931050	568523.122524	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	492830.260421
121	2020-07-31	498194.515194	420454.322198	575224.408685	420410.446443	576286.896165	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	498132.136420
122	2020-08-01	503536.313185	423990.499109	583472.812854	423474.062572	583517.930343	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	503598.135489
123	2020-08-02	508878.111176	427710.261822	590179.280639	426880.083705	589546.259190	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	509197.349655
124	2020-08-03	514219.909167	429818.513571	596802.158543	429548.237829	597121.105000	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	513997.756256
125	2020-08-04	519561.707157	432294.680528	604228.745002	433063.203140	605115.145228	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	519452.304689
126	2020-08-05	524903.505148	435909.640884	612432.818395	435984.147391	612031.192403	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	524938.835300
127	2020-08-06	530245.303139	440161.059044	619354.005783	438958.829135	619415.172563	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	530222.846356
128	2020-08-07	535587.101130	443689.648156	626241.717644	443904.203494	627152.008311	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	535524.722356
129	2020-08-08	540928.899120	446991.035146	634490.475828	447138.519762	634335.294673	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	540990.721425
130	2020-08-09	546270.697111	450669.151720	640936.158640	450325.304923	639952.325673	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	546589.935590
131	2020-08-10	551612.495102	454677.371220	647995.759576	453984.105336	646904.680074	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	551390.342191
132	2020-08-11	556954.293093	457636.567552	654722.409537	457250.668188	653853.469521	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	556844.890625
133	2020-08-12	562296.091083	460969.507798	661292.777720	460958.918879	660792.329198	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	562331.421236
134	2020-08-13	567637.889074	464670.664558	669053.621540	464797.069250	667665.723294	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	567615.432291
135	2020-08-14	572979.687065	467403.054504	675041.959218	467664.278889	674686.063687	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	572917.308291
136	2020-08-15	578321.485056	471343.443313	682796.567403	471193.345634	682333.820162	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	578383.307360
137	2020-08-16	583663.283046	473923.257430	689429.276571	473786.191408	689630.577336	319.238479	319.238479	319.238479	319.238479	319.238479	319.238479	583982.521526
138	2020-08-17	589005.081037	478242.712917	696218.368778	477249.500351	696766.913558	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	-222.152911	588782.928126
139	2020-08-18	594346.879028	481229.338261	703612.900872	480851.534754	703840.923099	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	-109.402468	594237.476560
140	2020-08-19	599688.677019	484723.590247	711071.956839	484484.949419	711176.963003	35.330152	35.330152	35.330152	35.330152	35.330152	35.330152	599724.007171
141	2020-08-20	605030.475010	487489.770446	718056.484471	488153.515186	718088.471704	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	-22.456783	605008.018227
142	2020-08-21	610372.273000	491742.387481	725863.670759	490996.917300	725416.597515	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	-62.378774	610309.894226
143	2020-08-22	615714.070991	494496.693145	734202.709035	494824.258263	733072.279946	61.822304	61.822304	61.822304	61.822304	61.822304	61.822304	615775.893295

	ds	trend	yhat_lower	yhat_upper	yhat
0	2020-04-01	1562.478044	440.134391	2705.934471	1597.808197
1	2020-04-02	2237.589341	1034.642193	3424.697178	2215.132558
2	2020-04-03	2912.700637	1593.587836	3999.316225	2850.321864
3	2020-04-04	3587.811933	2448.872845	4824.079486	3649.634237
4	2020-04-05	4262.923246	3282.597276	5717.911227	4582.161725
5	2020-04-06	4938.034559	3610.116626	5875.782594	4715.881648
6	2020-04-07	5613.557237	4332.059007	6617.467544	5504.154769
7	2020-04-08	6289.079916	5121.991510	7475.741192	6324.410068
8	2020-04-09	6964.888527	5764.247428	8058.687867	6942.431744
9	2020-04-10	7641.105899	6419.106369	8709.616752	7578.727125
10	2020-04-11	8317.323271	7271.478616	9472.300589	8379.145575
11	2020-04-12	9350.423222	8523.346750	10775.219594	9669.661701
12	2020-04-13	10383.523173	9059.127535	11271.647286	10161.370262
13	2020-04-14	11420.715229	10128.493831	12404.474412	11311.312761
14	2020-04-15	12459.491372	11376.004560	13725.012122	12494.821524
15	2020-04-16	13498.267514	12290.895406	14639.515867	13475.810731
16	2020-04-17	14539.482482	13298.366420	15615.946024	14477.103708
17	2020-04-18	15580.697450	14511.271692	16841.877709	15642.519754
18	2020-04-19	17074.725041	16201.063865	18472.646654	17393.963521
19	2020-04-20	18569.805190	17225.317921	19569.585432	18347.652279
20	2020-04-21	20064.885339	18732.222164	21123.151314	19955.482870
21	2020-04-22	21560.224801	20426.871059	22664.249893	21595.554953
22	2020-04-23	23055.564263	21888.210244	24201.274641	23033.107481
23	2020-04-24	24552.411091	23408.020268	25720.421802	24490.032317
24	2020-04-25	26049.257918	24896.855584	27295.947092	26111.080222
25	2020-04-26	27814.690142	26998.889314	29301.840256	28133.928621
26	2020-04-27	29580.695641	28205.591442	30551.669636	29358.542730
27	2020-04-28	31346.701140	30067.097644	32412.997284	31237.298672
28	2020-04-29	33113.325235	32019.270242	34302.767216	33148.655388
29	2020-04-30	34879.949331	33742.390857	36025.080427	34857.492548
30	2020-05-01	37153.300539	35923.091799	38272.404192	37090.921765
31	2020-05-02	40108.669027	39107.265683	41441.144751	40170.491331
32	2020-05-03	43064.037515	42317.075542	44578.058716	43383.275994
33	2020-05-04	46376.153248	44962.868596	47353.848413	46154.000337
34	2020-05-05	49688.268980	48444.117785	50649.532012	49578.866512
35	2020-05-06	53001.237170	51820.343181	54171.963036	53036.567322
36	2020-05-07	56314.270957	55234.699638	57402.993430	56291.814175
37	2020-05-08	59627.304745	58411.461735	60700.770653	59564.925971
38	2020-05-09	62940.338565	61778.952642	64102.832707	63002.160870
39	2020-05-10	66253.372386	65374.837665	67686.540616	66572.610865
40	2020-05-11	69566.406218	68197.174461	70472.763237	69344.253307
41	2020-05-12	72879.440071	71608.416637	73905.171848	72770.037603
42	2020-05-13	76192.473924	75076.169259	77362.875862	76227.804076
43	2020-05-14	81534.271915	80327.909869	82613.086202	81511.815132
44	2020-05-15	86876.069906	85765.343004	87843.251095	86813.691132
45	2020-05-16	92217.867896	91141.214712	93381.722915	92279.690201
46	2020-05-17	97559.665887	96698.804978	99057.519539	97878.904367
47	2020-05-18	102901.463878	101467.879787	103771.762262	102679.310967
48	2020-05-19	108243.261869	107012.301142	109269.511667	108133.859401
49	2020-05-20	113585.059859	112575.776950	114805.285674	113620.390012
50	2020-05-21	118926.857850	117676.952834	120088.135413	118904.401067
51	2020-05-22	124268.655841	123058.293191	125361.670745	124206.277067
52	2020-05-23	129610.453832	128474.002813	130878.098212	129672.276136
53	2020-05-24	134952.251823	134040.065671	136373.079329	135271.490302
54	2020-05-25	140294.049813	138834.800789	141206.219064	140071.896902
55	2020-05-26	145635.847804	144332.255357	146784.975278	145526.445336
56	2020-05-27	150977.645795	149695.997101	152300.431377	151012.975947
57	2020-05-28	156319.443786	154726.107375	157759.669729	156296.987003
58	2020-05-29	161661.241776	159798.336317	163415.065260	161598.863002
59	2020-05-30	167003.039767	164900.636692	168938.399581	167064.862071
60	2020-05-31	172344.837758	169954.023235	175097.897972	172664.076237
61	2020-06-01	177686.635749	174364.053397	180249.856038	177464.482838
62	2020-06-02	183028.433739	179136.459892	186381.581877	182919.031271
63	2020-06-03	188370.231730	184105.292071	192265.986806	188405.561882
64	2020-06-04	193712.029721	188742.230797	198289.932625	193689.572938
65	2020-06-05	199053.827712	193359.065854	204065.962930	198991.448938
66	2020-06-06	204395.625702	198191.660663	210352.396191	204457.448007
67	2020-06-07	209737.423693	203112.309328	216791.735624	210056.662172
68	2020-06-08	215079.221684	207313.820199	222245.863465	214857.068773
69	2020-06-09	220421.019675	211676.990344	228580.825435	220311.617207
70	2020-06-10	225762.817665	216772.320285	235021.840862	225798.147818
71	2020-06-11	231104.615656	221193.811300	240941.529820	231082.158873
72	2020-06-12	236446.413647	225396.034728	247282.971939	236384.034873
73	2020-06-13	241788.211638	230001.430264	253894.376628	241850.033942
74	2020-06-14	247130.009629	234908.101070	260550.491259	247449.248108
75	2020-06-15	252471.807619	238774.520813	266144.206152	252249.654708
76	2020-06-16	257813.605610	243083.598379	272263.139253	257704.203142
77	2020-06-17	263155.403601	247950.194877	278853.422423	263190.733753
78	2020-06-18	268497.201592	251929.981926	284658.199534	268474.744809
79	2020-06-19	273838.999582	256068.388171	291051.162361	273776.620808
80	2020-06-20	279180.797573	260255.471779	298124.645436	279242.619877
81	2020-06-21	284522.595564	264949.933831	304250.664411	284841.834043
82	2020-06-22	289864.393555	268200.598124	310034.725701	289642.240644
83	2020-06-23	295206.191545	273114.052177	316149.014826	295096.789077
84	2020-06-24	300547.989536	277393.710867	323248.677369	300583.319688
85	2020-06-25	305889.787527	281775.432075	329728.601047	305867.330744
86	2020-06-26	311231.585518	285845.406937	336141.774449	311169.206744
87	2020-06-27	316573.383508	290196.368269	342729.917248	316635.205813
88	2020-06-28	321915.181499	295226.082647	349181.491201	322234.419978
89	2020-06-29	327256.979490	297938.378231	354818.488081	327034.826579
90	2020-06-30	332598.777481	302665.794443	362216.539980	332489.375013
91	2020-07-01	337940.575471	307154.440032	368533.463540	337975.905624
92	2020-07-02	343282.373462	310469.244568	374779.996800	343259.916679
93	2020-07-03	348624.171453	314390.389501	381729.826374	348561.792679
94	2020-07-04	353965.969444	318007.920114	388725.138101	354027.791748
95	2020-07-05	359307.767434	322730.421822	395716.021872	359627.005914
96	2020-07-06	364649.565425	325908.688693	401849.106220	364427.412514
97	2020-07-07	369991.363416	330321.348559	408884.701987	369881.960948
98	2020-07-08	375333.161407	334391.498173	415319.993385	375368.491559
99	2020-07-09	380674.959398	338575.623560	422458.895341	380652.502615
100	2020-07-10	386016.757388	342806.631575	429505.407082	385954.378614
101	2020-07-11	391358.555379	347592.406139	436903.793843	391420.377683
102	2020-07-12	396700.353370	350873.159068	443262.863755	397019.591849
103	2020-07-13	402042.151361	354110.369105	450218.733937	401819.998450
104	2020-07-14	407383.949351	358715.241542	456294.525478	407274.546883
105	2020-07-15	412725.747342	362924.354884	463762.548022	412761.077494
106	2020-07-16	418067.545333	367125.791351	470003.918844	418045.088550
107	2020-07-17	423409.343324	371256.560499	477219.652589	423346.964550
108	2020-07-18	428751.141314	374521.132797	483957.415499	428812.963619
109	2020-07-19	434092.939305	378124.567718	491051.135208	434412.177784
110	2020-07-20	439434.737296	381608.662638	497575.119169	439212.584385
111	2020-07-21	444776.535287	385517.915238	504785.693662	444667.132819
112	2020-07-22	450118.333277	388871.804832	511748.572767	450153.663430
113	2020-07-23	455460.131268	393345.143974	518362.270241	455437.674485
114	2020-07-24	460801.929259	396309.083492	526530.140740	460739.550485
115	2020-07-25	466143.727250	400090.593839	533052.499856	466205.549554
116	2020-07-26	471485.525240	404242.216051	541117.739535	471804.763720
117	2020-07-27	476827.323231	406251.310414	547263.381340	476605.170320
118	2020-07-28	482169.121222	408320.535371	554624.248012	482059.718754
119	2020-07-29	487510.919213	412760.648468	561330.471883	487546.249365
120	2020-07-30	492852.717204	415654.332870	568785.045544	492830.260421
121	2020-07-31	498194.515194	420454.322198	575224.408685	498132.136420
122	2020-08-01	503536.313185	423990.499109	583472.812854	503598.135489
123	2020-08-02	508878.111176	427710.261822	590179.280639	509197.349655
124	2020-08-03	514219.909167	429818.513571	596802.158543	513997.756256
125	2020-08-04	519561.707157	432294.680528	604228.745002	519452.304689
126	2020-08-05	524903.505148	435909.640884	612432.818395	524938.835300
127	2020-08-06	530245.303139	440161.059044	619354.005783	530222.846356
128	2020-08-07	535587.101130	443689.648156	626241.717644	535524.722356
129	2020-08-08	540928.899120	446991.035146	634490.475828	540990.721425
130	2020-08-09	546270.697111	450669.151720	640936.158640	546589.935590
131	2020-08-10	551612.495102	454677.371220	647995.759576	551390.342191
132	2020-08-11	556954.293093	457636.567552	654722.409537	556844.890625
133	2020-08-12	562296.091083	460969.507798	661292.777720	562331.421236
134	2020-08-13	567637.889074	464670.664558	669053.621540	567615.432291
135	2020-08-14	572979.687065	467403.054504	675041.959218	572917.308291
136	2020-08-15	578321.485056	471343.443313	682796.567403	578383.307360
137	2020-08-16	583663.283046	473923.257430	689429.276571	583982.521526
138	2020-08-17	589005.081037	478242.712917	696218.368778	588782.928126
139	2020-08-18	594346.879028	481229.338261	703612.900872	594237.476560
140	2020-08-19	599688.677019	484723.590247	711071.956839	599724.007171
141	2020-08-20	605030.475010	487489.770446	718056.484471	605008.018227
142	2020-08-21	610372.273000	491742.387481	725863.670759	610309.894226
143	2020-08-22	615714.070991	494496.693145	734202.709035	615775.893295

	State	Statecode	Confirmed	Active	Recovered	Deaths	Last Updated	Latitude	Longitude
0	Maharashtra	MH	50231	33996	14600	1635	24-05-2020 22:25	19.7515	75.7139
1	Tamil Nadu	TN	16277	7841	8324	112	24-05-2020 19:21	11.1271	78.6569
2	Gujarat	GJ	14063	6793	6412	858	24-05-2020 20:44	22.2587	71.1924
3	Delhi	DL	13418	6617	6540	261	24-05-2020 14:29	28.7041	77.1025
4	Rajasthan	RJ	7100	3081	3856	163	25-05-2020 10:07	27.0238	74.2179
5	Madhya Pradesh	MP	6665	2967	3408	290	24-05-2020 21:44	22.9734	78.6569
6	Uttar Pradesh	UP	6268	2569	3538	161	24-05-2020 23:33	26.8467	80.9462
7	West Bengal	WB	3667	2056	1339	272	24-05-2020 20:47	22.9868	87.8550
8	Andhra Pradesh	AP	2780	883	1841	56	24-05-2020 15:22	15.9129	79.7400
9	State Unassigned	UN	2642	2642	0	0	25-05-2020 09:33	NaN	NaN
10	Bihar	BR	2574	1861	702	11	24-05-2020 23:43	25.0961	85.3131
11	Karnataka	KA	2089	1391	654	42	24-05-2020 18:23	15.3173	75.7139
12	Punjab	PB	2060	122	1898	40	24-05-2020 22:45	31.1471	75.3412
13	Telangana	TG	1854	709	1092	53	24-05-2020 21:22	18.1124	79.0193
14	Jammu and Kashmir	JK	1621	791	809	21	24-05-2020 21:11	33.7782	76.5762
15	Odisha	OR	1336	779	550	7	24-05-2020 15:32	20.9517	85.0985
16	Haryana	HR	1184	403	765	16	24-05-2020 22:13	29.0588	76.0856
17	Kerala	KL	848	322	520	6	24-05-2020 20:01	10.8505	76.2711
18	Assam	AS	428	363	58	4	25-05-2020 10:21	26.2006	92.9376
19	Jharkhand	JH	370	218	148	4	24-05-2020 22:45	23.6102	85.2799
20	Uttarakhand	UT	317	255	58	3	24-05-2020 20:44	30.0668	79.0193
21	Chandigarh	CH	262	79	179	4	24-05-2020 23:20	30.7333	76.7794
22	Chhattisgarh	CT	252	188	64	0	24-05-2020 23:33	21.2787	81.8661
23	Himachal Pradesh	HP	203	137	59	4	24-05-2020 22:23	31.1048	77.1734
24	Tripura	TR	194	29	165	0	24-05-2020 23:43	23.9408	91.9882
25	Goa	GA	66	50	16	0	24-05-2020 11:47	15.2993	74.1240
26	Ladakh	LA	52	9	43	0	24-05-2020 14:52	34.2996	78.2932
27	Puducherry	PY	41	29	12	0	24-05-2020 23:01	11.9416	79.8083
28	Andaman and Nicobar Islands	AN	33	0	33	0	07-05-2020 22:24	11.7401	92.6586
29	Manipur	MN	32	30	2	0	24-05-2020 15:00	24.6637	93.9063
30	Meghalaya	ML	14	1	12	1	20-05-2020 22:48	25.4670	91.3662
31	Dadra and Nagar Haveli and Daman and Diu	DN	2	1	1	0	23-05-2020 23:47	20.2762	73.0083
32	Arunachal Pradesh	AR	2	1	1	0	24-05-2020 23:43	28.2180	94.7278
33	Mizoram	MZ	1	0	1	0	05-05-2020 22:32	23.1645	92.9376
34	Sikkim	SK	1	1	0	0	23-05-2020 19:42	27.3389	88.6065
35	Nagaland	NL	0	0	0	0	20-04-2020 08:45	26.1584	94.5624
36	Lakshadweep	LD	0	0	0	0	26-03-2020 07:19	10.0760	73.6303

	Date	Daily Confirmed	Daily Deaths	Daily Recovered	Total Confirmed	Total Deaths	Total Recovered	Total Active
0	2020-01-30	1	0	0	1	0	0	1
1	2020-01-31	0	0	0	1	0	0	1
2	2020-02-01	0	0	0	1	0	0	1
3	2020-02-02	1	0	0	2	0	0	2
4	2020-02-03	1	0	0	3	0	0	3
5	2020-02-04	0	0	0	3	0	0	3
6	2020-02-05	0	0	0	3	0	0	3
7	2020-02-06	0	0	0	3	0	0	3
8	2020-02-07	0	0	0	3	0	0	3
9	2020-02-08	0	0	0	3	0	0	3
10	2020-02-09	0	0	0	3	0	0	3
11	2020-02-10	0	0	0	3	0	0	3
12	2020-02-11	0	0	0	3	0	0	3
13	2020-02-12	0	0	0	3	0	0	3
14	2020-02-13	0	0	1	3	0	1	2
15	2020-02-14	0	0	0	3	0	1	2
16	2020-02-15	0	0	0	3	0	1	2
17	2020-02-16	0	0	1	3	0	2	1
18	2020-02-17	0	0	0	3	0	2	1
19	2020-02-18	0	0	0	3	0	2	1
20	2020-02-19	0	0	0	3	0	2	1
21	2020-02-20	0	0	1	3	0	3	0
22	2020-02-21	0	0	0	3	0	3	0
23	2020-02-22	0	0	0	3	0	3	0
24	2020-02-23	0	0	0	3	0	3	0
25	2020-02-24	0	0	0	3	0	3	0
26	2020-02-25	0	0	0	3	0	3	0
27	2020-02-26	0	0	0	3	0	3	0
28	2020-02-27	0	0	0	3	0	3	0
29	2020-02-28	0	0	0	3	0	3	0
30	2020-02-29	0	0	0	3	0	3	0
31	2020-03-01	0	0	0	3	0	3	0
32	2020-03-02	2	0	0	5	0	3	2
33	2020-03-03	1	0	0	6	0	3	3
34	2020-03-04	22	0	0	28	0	3	25
35	2020-03-05	2	0	0	30	0	3	27
36	2020-03-06	1	0	0	31	0	3	28
37	2020-03-07	3	0	0	34	0	3	31
38	2020-03-08	5	0	0	39	0	3	36
39	2020-03-09	9	0	0	48	0	3	45
40	2020-03-10	15	0	1	63	0	4	59
41	2020-03-11	8	0	0	71	0	4	67
42	2020-03-12	10	1	0	81	1	4	76
43	2020-03-13	10	0	6	91	1	10	80
44	2020-03-14	11	1	0	102	2	10	90
45	2020-03-15	10	0	3	112	2	13	97
46	2020-03-16	14	0	1	126	2	14	110
47	2020-03-17	20	1	1	146	3	15	128
48	2020-03-18	25	0	0	171	3	15	153
49	2020-03-19	27	1	5	198	4	20	174
50	2020-03-20	58	0	3	256	4	23	229
51	2020-03-21	78	0	0	334	4	23	307
52	2020-03-22	69	3	0	403	7	23	373
53	2020-03-23	94	2	2	497	9	25	463
54	2020-03-24	74	1	15	571	10	40	521
55	2020-03-25	86	1	3	657	11	43	603
56	2020-03-26	73	5	7	730	16	50	664
57	2020-03-27	153	3	25	883	19	75	789
58	2020-03-28	136	5	10	1019	24	85	910
59	2020-03-29	120	3	17	1139	27	102	1010
60	2020-03-30	187	14	35	1326	41	137	1148
61	2020-03-31	309	6	13	1635	47	150	1438
62	2020-04-01	424	6	19	2059	53	169	1837
63	2020-04-02	486	16	22	2545	69	191	2285
64	2020-04-03	560	14	39	3105	83	230	2792
65	2020-04-04	579	13	56	3684	96	286	3302
66	2020-04-05	609	22	43	4293	118	329	3846
67	2020-04-06	484	16	65	4777	134	394	4249
68	2020-04-07	573	27	75	5350	161	469	4720
69	2020-04-08	565	20	96	5915	181	565	5169
70	2020-04-09	813	46	70	6728	227	635	5866
71	2020-04-10	871	22	151	7599	249	786	6564
72	2020-04-11	854	41	186	8453	290	972	7191
73	2020-04-12	758	42	114	9211	332	1086	7793
74	2020-04-13	1243	27	112	10454	359	1198	8897
75	2020-04-14	1031	37	167	11485	396	1365	9724
76	2020-04-15	886	27	144	12371	423	1509	10439
77	2020-04-16	1061	26	258	13432	449	1767	11216
78	2020-04-17	922	38	273	14354	487	2040	11827
79	2020-04-18	1371	35	426	15725	522	2466	12737
80	2020-04-19	1580	38	388	17305	560	2854	13891
81	2020-04-20	1239	33	419	18544	593	3273	14678
82	2020-04-21	1537	53	703	20081	646	3976	15459
83	2020-04-22	1292	36	394	21373	682	4370	16321
84	2020-04-23	1667	40	642	23040	722	5012	17306
85	2020-04-24	1408	59	484	24448	781	5496	18171
86	2020-04-25	1835	44	442	26283	825	5938	19520
87	2020-04-26	1607	56	585	27890	881	6523	20486
88	2020-04-27	1568	58	580	29458	939	7103	21416
89	2020-04-28	1902	69	636	31360	1008	7739	22613
90	2020-04-29	1705	71	690	33065	1079	8429	23557
91	2020-04-30	1801	75	630	34866	1154	9059	24653
92	2020-05-01	2396	77	962	37262	1231	10021	26010
93	2020-05-02	2564	92	831	39826	1323	10852	27651
94	2020-05-03	2952	140	911	42778	1463	11763	29552
95	2020-05-04	3656	103	1082	46434	1566	12845	32023
96	2020-05-05	2971	128	1295	49405	1694	14140	33571
97	2020-05-06	3602	91	1161	53007	1785	15301	35921
98	2020-05-07	3344	104	1475	56351	1889	16776	37686
99	2020-05-08	3339	97	1111	59690	1986	17887	39817
100	2020-05-09	3175	115	1414	62865	2101	19301	41463
101	2020-05-10	4311	112	1669	67176	2213	20970	43993
102	2020-05-11	3592	81	1579	70768	2294	22549	45925
103	2020-05-12	3562	120	1905	74330	2414	24454	47462
104	2020-05-13	3726	137	1963	78056	2551	26417	49088
105	2020-05-14	3991	97	1594	82047	2648	28011	51388
106	2020-05-15	3808	104	2234	85855	2752	30245	52858
107	2020-05-16	4794	120	4012	90649	2872	34257	53520
108	2020-05-17	5049	152	2538	95698	3024	36795	55879
109	2020-05-18	4628	131	2482	100326	3155	39277	57894
110	2020-05-19	6154	146	3032	106480	3301	42309	60870
111	2020-05-20	5720	134	3113	112200	3435	45422	63343
112	2020-05-21	6023	148	3131	118223	3583	48553	66087
113	2020-05-22	6536	142	3280	124759	3725	51833	69201
114	2020-05-23	6665	142	2576	131422	3867	54409	73146
115	2020-05-24	7111	156	3283	138535	4023	57692	76820

	Date	Daily Confirmed	Daily Deaths	Daily Recovered	Total Confirmed	Total Deaths	Total Recovered	Total Active	Year	Month	Week	Day
0	2020-01-30	1	0	0	1	0	0	1	2020	1	5	30
1	2020-01-31	0	0	0	1	0	0	1	2020	1	5	31
2	2020-02-01	0	0	0	1	0	0	1	2020	2	5	1
3	2020-02-02	1	0	0	2	0	0	2	2020	2	5	2
4	2020-02-03	1	0	0	3	0	0	3	2020	2	6	3
5	2020-02-04	0	0	0	3	0	0	3	2020	2	6	4
6	2020-02-05	0	0	0	3	0	0	3	2020	2	6	5
7	2020-02-06	0	0	0	3	0	0	3	2020	2	6	6
8	2020-02-07	0	0	0	3	0	0	3	2020	2	6	7
9	2020-02-08	0	0	0	3	0	0	3	2020	2	6	8
10	2020-02-09	0	0	0	3	0	0	3	2020	2	6	9
11	2020-02-10	0	0	0	3	0	0	3	2020	2	7	10
12	2020-02-11	0	0	0	3	0	0	3	2020	2	7	11
13	2020-02-12	0	0	0	3	0	0	3	2020	2	7	12
14	2020-02-13	0	0	1	3	0	1	2	2020	2	7	13
15	2020-02-14	0	0	0	3	0	1	2	2020	2	7	14
16	2020-02-15	0	0	0	3	0	1	2	2020	2	7	15
17	2020-02-16	0	0	1	3	0	2	1	2020	2	7	16
18	2020-02-17	0	0	0	3	0	2	1	2020	2	8	17
19	2020-02-18	0	0	0	3	0	2	1	2020	2	8	18
20	2020-02-19	0	0	0	3	0	2	1	2020	2	8	19
21	2020-02-20	0	0	1	3	0	3	0	2020	2	8	20
22	2020-02-21	0	0	0	3	0	3	0	2020	2	8	21
23	2020-02-22	0	0	0	3	0	3	0	2020	2	8	22
24	2020-02-23	0	0	0	3	0	3	0	2020	2	8	23
25	2020-02-24	0	0	0	3	0	3	0	2020	2	9	24
26	2020-02-25	0	0	0	3	0	3	0	2020	2	9	25
27	2020-02-26	0	0	0	3	0	3	0	2020	2	9	26
28	2020-02-27	0	0	0	3	0	3	0	2020	2	9	27
29	2020-02-28	0	0	0	3	0	3	0	2020	2	9	28
30	2020-02-29	0	0	0	3	0	3	0	2020	2	9	29
31	2020-03-01	0	0	0	3	0	3	0	2020	3	9	1
32	2020-03-02	2	0	0	5	0	3	2	2020	3	10	2
33	2020-03-03	1	0	0	6	0	3	3	2020	3	10	3
34	2020-03-04	22	0	0	28	0	3	25	2020	3	10	4
35	2020-03-05	2	0	0	30	0	3	27	2020	3	10	5
36	2020-03-06	1	0	0	31	0	3	28	2020	3	10	6
37	2020-03-07	3	0	0	34	0	3	31	2020	3	10	7
38	2020-03-08	5	0	0	39	0	3	36	2020	3	10	8
39	2020-03-09	9	0	0	48	0	3	45	2020	3	11	9
40	2020-03-10	15	0	1	63	0	4	59	2020	3	11	10
41	2020-03-11	8	0	0	71	0	4	67	2020	3	11	11
42	2020-03-12	10	1	0	81	1	4	76	2020	3	11	12
43	2020-03-13	10	0	6	91	1	10	80	2020	3	11	13
44	2020-03-14	11	1	0	102	2	10	90	2020	3	11	14
45	2020-03-15	10	0	3	112	2	13	97	2020	3	11	15
46	2020-03-16	14	0	1	126	2	14	110	2020	3	12	16
47	2020-03-17	20	1	1	146	3	15	128	2020	3	12	17
48	2020-03-18	25	0	0	171	3	15	153	2020	3	12	18
49	2020-03-19	27	1	5	198	4	20	174	2020	3	12	19
50	2020-03-20	58	0	3	256	4	23	229	2020	3	12	20
51	2020-03-21	78	0	0	334	4	23	307	2020	3	12	21
52	2020-03-22	69	3	0	403	7	23	373	2020	3	12	22
53	2020-03-23	94	2	2	497	9	25	463	2020	3	13	23
54	2020-03-24	74	1	15	571	10	40	521	2020	3	13	24
55	2020-03-25	86	1	3	657	11	43	603	2020	3	13	25
56	2020-03-26	73	5	7	730	16	50	664	2020	3	13	26
57	2020-03-27	153	3	25	883	19	75	789	2020	3	13	27
58	2020-03-28	136	5	10	1019	24	85	910	2020	3	13	28
59	2020-03-29	120	3	17	1139	27	102	1010	2020	3	13	29
60	2020-03-30	187	14	35	1326	41	137	1148	2020	3	14	30
61	2020-03-31	309	6	13	1635	47	150	1438	2020	3	14	31
62	2020-04-01	424	6	19	2059	53	169	1837	2020	4	14	1
63	2020-04-02	486	16	22	2545	69	191	2285	2020	4	14	2
64	2020-04-03	560	14	39	3105	83	230	2792	2020	4	14	3
65	2020-04-04	579	13	56	3684	96	286	3302	2020	4	14	4
66	2020-04-05	609	22	43	4293	118	329	3846	2020	4	14	5
67	2020-04-06	484	16	65	4777	134	394	4249	2020	4	15	6
68	2020-04-07	573	27	75	5350	161	469	4720	2020	4	15	7
69	2020-04-08	565	20	96	5915	181	565	5169	2020	4	15	8
70	2020-04-09	813	46	70	6728	227	635	5866	2020	4	15	9
71	2020-04-10	871	22	151	7599	249	786	6564	2020	4	15	10
72	2020-04-11	854	41	186	8453	290	972	7191	2020	4	15	11
73	2020-04-12	758	42	114	9211	332	1086	7793	2020	4	15	12
74	2020-04-13	1243	27	112	10454	359	1198	8897	2020	4	16	13
75	2020-04-14	1031	37	167	11485	396	1365	9724	2020	4	16	14
76	2020-04-15	886	27	144	12371	423	1509	10439	2020	4	16	15
77	2020-04-16	1061	26	258	13432	449	1767	11216	2020	4	16	16
78	2020-04-17	922	38	273	14354	487	2040	11827	2020	4	16	17
79	2020-04-18	1371	35	426	15725	522	2466	12737	2020	4	16	18
80	2020-04-19	1580	38	388	17305	560	2854	13891	2020	4	16	19
81	2020-04-20	1239	33	419	18544	593	3273	14678	2020	4	17	20
82	2020-04-21	1537	53	703	20081	646	3976	15459	2020	4	17	21
83	2020-04-22	1292	36	394	21373	682	4370	16321	2020	4	17	22
84	2020-04-23	1667	40	642	23040	722	5012	17306	2020	4	17	23
85	2020-04-24	1408	59	484	24448	781	5496	18171	2020	4	17	24
86	2020-04-25	1835	44	442	26283	825	5938	19520	2020	4	17	25
87	2020-04-26	1607	56	585	27890	881	6523	20486	2020	4	17	26
88	2020-04-27	1568	58	580	29458	939	7103	21416	2020	4	18	27
89	2020-04-28	1902	69	636	31360	1008	7739	22613	2020	4	18	28
90	2020-04-29	1705	71	690	33065	1079	8429	23557	2020	4	18	29
91	2020-04-30	1801	75	630	34866	1154	9059	24653	2020	4	18	30
92	2020-05-01	2396	77	962	37262	1231	10021	26010	2020	5	18	1
93	2020-05-02	2564	92	831	39826	1323	10852	27651	2020	5	18	2
94	2020-05-03	2952	140	911	42778	1463	11763	29552	2020	5	18	3
95	2020-05-04	3656	103	1082	46434	1566	12845	32023	2020	5	19	4
96	2020-05-05	2971	128	1295	49405	1694	14140	33571	2020	5	19	5
97	2020-05-06	3602	91	1161	53007	1785	15301	35921	2020	5	19	6
98	2020-05-07	3344	104	1475	56351	1889	16776	37686	2020	5	19	7
99	2020-05-08	3339	97	1111	59690	1986	17887	39817	2020	5	19	8
100	2020-05-09	3175	115	1414	62865	2101	19301	41463	2020	5	19	9
101	2020-05-10	4311	112	1669	67176	2213	20970	43993	2020	5	19	10
102	2020-05-11	3592	81	1579	70768	2294	22549	45925	2020	5	20	11
103	2020-05-12	3562	120	1905	74330	2414	24454	47462	2020	5	20	12
104	2020-05-13	3726	137	1963	78056	2551	26417	49088	2020	5	20	13
105	2020-05-14	3991	97	1594	82047	2648	28011	51388	2020	5	20	14
106	2020-05-15	3808	104	2234	85855	2752	30245	52858	2020	5	20	15
107	2020-05-16	4794	120	4012	90649	2872	34257	53520	2020	5	20	16
108	2020-05-17	5049	152	2538	95698	3024	36795	55879	2020	5	20	17
109	2020-05-18	4628	131	2482	100326	3155	39277	57894	2020	5	21	18
110	2020-05-19	6154	146	3032	106480	3301	42309	60870	2020	5	21	19
111	2020-05-20	5720	134	3113	112200	3435	45422	63343	2020	5	21	20
112	2020-05-21	6023	148	3131	118223	3583	48553	66087	2020	5	21	21
113	2020-05-22	6536	142	3280	124759	3725	51833	69201	2020	5	21	22
114	2020-05-23	6665	142	2576	131422	3867	54409	73146	2020	5	21	23
115	2020-05-24	7111	156	3283	138535	4023	57692	76820	2020	5	21	24

	Week
99	19
88	18
91	18
87	17
111	21
67	15
114	21
75	16
97	19
98	19
66	14
79	16
93	18
84	17
105	20
81	17
80	16
92	18
70	15
90	18
112	21
78	16
115	21
102	20
106	20
113	21
71	15
89	18
94	18
95	19
77	16
76	16
104	20
86	17
107	20
103	20
63	14
69	15
74	16
65	14
108	20
68	15
83	17
64	14
72	15
82	17
62	14
109	21

	Country	Confirmed	Deaths	Recovered	Active	Critical	Tot Cases/1M pop	Deaths/1M pop	TotalTests	Tests/ 1M pop	Population
0	USA	1686436	99300.0	451702.0	1135434.0	17135.0	5098.0	300.00	14749756.0	44587.0	3.308064e+08
1	Brazil	365213	22746.0	149911.0	192556.0	8318.0	1719.0	107.00	735224.0	3461.0	2.124057e+08
2	Russia	344481	3541.0	113299.0	227641.0	2300.0	2361.0	24.00	8685305.0	59518.0	1.459283e+08
3	Spain	282852	28752.0	196958.0	57142.0	854.0	6050.0	615.00	3556567.0	76071.0	4.675300e+07
4	UK	259559	36793.0	NaN	NaN	1559.0	3825.0	542.00	3458905.0	50979.0	6.785008e+07
5	Italy	229858	32785.0	140479.0	56594.0	553.0	3801.0	542.00	3447012.0	57003.0	6.047047e+07
6	France	182584	28367.0	64617.0	89600.0	1655.0	2798.0	435.00	1384633.0	21217.0	6.525919e+07
7	Germany	180328	8371.0	160300.0	11657.0	889.0	2153.0	100.00	3595059.0	42922.0	8.375724e+07
8	Turkey	156827	4340.0	118694.0	33793.0	769.0	1862.0	52.00	1832262.0	21749.0	8.424494e+07
9	India	138917	4024.0	57721.0	77172.0	8944.0	101.0	3.00	3033591.0	2200.0	1.378604e+09
10	Iran	135701	7417.0	105801.0	22483.0	2615.0	1618.0	88.00	800519.0	9544.0	8.388027e+07
11	Peru	119959	3456.0	49795.0	66708.0	920.0	3644.0	105.00	820967.0	24936.0	3.292343e+07
12	Canada	84699	6424.0	43985.0	34290.0	502.0	2246.0	170.00	1459288.0	38700.0	3.770819e+07
13	China	82985	4634.0	78268.0	83.0	7.0	58.0	3.00	NaN	NaN	1.439324e+09
14	Saudi Arabia	72560	390.0	43520.0	28650.0	372.0	2088.0	11.00	703534.0	20242.0	3.475622e+07
15	Chile	69102	718.0	28148.0	40236.0	1090.0	3618.0	38.00	471758.0	24700.0	1.909937e+07
16	Mexico	68620	7394.0	47424.0	13802.0	378.0	533.0	57.00	219164.0	1702.0	1.287924e+08
17	Belgium	57092	9280.0	15272.0	32540.0	256.0	4928.0	801.00	781284.0	67442.0	1.158456e+07
18	Pakistan	56349	1167.0	17482.0	37700.0	111.0	256.0	5.00	483656.0	2194.0	2.204272e+08
19	Netherlands	45236	5822.0	NaN	NaN	223.0	2641.0	340.00	313755.0	18315.0	1.713111e+07
20	Qatar	43714	23.0	9170.0	34521.0	188.0	15200.0	8.00	188143.0	65422.0	2.875845e+06
21	Ecuador	36756	3108.0	3560.0	30088.0	208.0	2087.0	176.00	106079.0	6022.0	1.761463e+07
22	Belarus	36198	199.0	14155.0	21844.0	92.0	3831.0	21.00	450627.0	47687.0	9.449627e+06
23	Bangladesh	33610	480.0	6901.0	26229.0	1.0	204.0	3.00	243583.0	1481.0	1.645199e+08
24	Sweden	33459	3998.0	4971.0	24490.0	249.0	3315.0	396.00	209900.0	20797.0	1.009289e+07
25	Singapore	31616	23.0	14876.0	16717.0	8.0	5408.0	4.00	294414.0	50365.0	5.845641e+06
26	Switzerland	30736	1906.0	28100.0	730.0	50.0	3554.0	220.00	370464.0	42837.0	8.648175e+06
27	Portugal	30623	1316.0	17549.0	11758.0	78.0	3002.0	129.00	689705.0	67621.0	1.019958e+07
28	UAE	29485	245.0	15056.0	14184.0	1.0	2985.0	25.00	1600923.0	162071.0	9.877923e+06
29	Ireland	24639	1608.0	21060.0	1971.0	54.0	4996.0	326.00	295626.0	59940.0	4.932053e+06
30	South Africa	22583	429.0	11100.0	11054.0	128.0	381.0	7.00	583855.0	9857.0	5.923039e+07
31	Indonesia	22271	1372.0	5402.0	15497.0	NaN	82.0	5.00	248555.0	910.0	2.732239e+08
32	Poland	21326	996.0	9194.0	11136.0	160.0	563.0	26.00	767441.0	20276.0	3.785065e+07
33	Kuwait	21302	156.0	6117.0	15029.0	177.0	4996.0	37.00	271089.0	63578.0	4.263883e+06
34	Colombia	21175	727.0	5016.0	15432.0	136.0	417.0	14.00	252742.0	4973.0	5.082667e+07
35	Ukraine	20986	617.0	7108.0	13261.0	256.0	480.0	14.00	285626.0	6527.0	4.375870e+07
36	Romania	18070	1185.0	11399.0	5486.0	188.0	939.0	62.00	368482.0	19142.0	1.924983e+07
37	Egypt	17265	764.0	4807.0	11694.0	41.0	169.0	7.00	135000.0	1322.0	1.021257e+08
38	Israel	16717	279.0	14153.0	2285.0	45.0	1818.0	30.00	537489.0	58438.0	9.197590e+06
39	Japan	16550	820.0	13413.0	2317.0	168.0	131.0	6.00	271201.0	2144.0	1.265138e+08
40	Austria	16503	640.0	15063.0	800.0	29.0	1833.0	71.00	401857.0	44645.0	9.001207e+06
41	Dominican Republic	14801	458.0	8133.0	6210.0	113.0	1366.0	42.00	65355.0	6031.0	1.083667e+07
42	Philippines	14035	868.0	3249.0	9918.0	81.0	128.0	8.00	295593.0	2701.0	1.094278e+08
43	Argentina	12076	452.0	3732.0	7892.0	171.0	267.0	10.00	129418.0	2866.0	4.515311e+07
44	Denmark	11360	562.0	9900.0	898.0	21.0	1962.0	97.00	537742.0	92872.0	5.790165e+06
45	S. Korea	11206	267.0	10226.0	713.0	15.0	219.0	5.00	826437.0	16121.0	5.126484e+07
46	Serbia	11159	238.0	5857.0	5064.0	12.0	1277.0	27.00	217856.0	24924.0	8.740747e+06
47	Panama	10926	306.0	6279.0	4341.0	72.0	2536.0	71.00	58240.0	13520.0	4.307539e+06
48	Afghanistan	10582	218.0	1075.0	9289.0	19.0	273.0	6.00	30052.0	774.0	3.883176e+07
49	Bahrain	9138	14.0	4587.0	4537.0	8.0	5392.0	8.00	276552.0	163192.0	1.694642e+06
50	Czechia	8955	315.0	6078.0	2562.0	29.0	836.0	29.00	399896.0	37349.0	1.070701e+07
51	Kazakhstan	8531	35.0	4352.0	4144.0	31.0	455.0	2.00	671774.0	35822.0	1.875327e+07
52	Norway	8352	235.0	7727.0	390.0	12.0	1542.0	43.00	229769.0	42417.0	5.416911e+06
53	Algeria	8306	600.0	4784.0	2922.0	22.0	190.0	14.00	NaN	NaN	4.376577e+07
54	Nigeria	7839	226.0	2263.0	5350.0	7.0	38.0	1.00	44458.0	216.0	2.055702e+08
55	Oman	7770	37.0	1933.0	5800.0	31.0	1526.0	7.00	72000.0	14140.0	5.092104e+06
56	Morocco	7433	199.0	4703.0	2531.0	1.0	202.0	5.00	142882.0	3876.0	3.686493e+07
57	Malaysia	7245	115.0	5945.0	1185.0	9.0	224.0	4.00	507682.0	15707.0	3.232253e+07
58	Australia	7114	102.0	6531.0	481.0	5.0	279.0	4.00	1243157.0	48810.0	2.546906e+07
59	Moldova	7093	250.0	3713.0	3130.0	286.0	1758.0	62.00	40565.0	10054.0	4.034871e+06
60	Ghana	6683	32.0	1998.0	4653.0	16.0	216.0	1.00	193705.0	6248.0	3.100208e+07
61	Armenia	6661	81.0	3064.0	3516.0	10.0	2248.0	27.00	50397.0	17011.0	2.962695e+06
62	Finland	6579	307.0	4800.0	1472.0	19.0	1188.0	55.00	166900.0	30127.0	5.539869e+06
63	Bolivia	6263	250.0	629.0	5384.0	3.0	537.0	21.00	22294.0	1913.0	1.165626e+07
64	Cameroon	4890	165.0	1865.0	2860.0	28.0	185.0	6.00	NaN	NaN	2.647218e+07
65	Iraq	4469	160.0	2738.0	1571.0	NaN	111.0	4.00	186885.0	4658.0	4.012309e+07
66	Azerbaijan	4122	49.0	2607.0	1466.0	42.0	407.0	5.00	270739.0	26727.0	1.012978e+07
67	Luxembourg	3992	110.0	3767.0	115.0	7.0	6388.0	176.00	67729.0	108385.0	6.248910e+05
68	Honduras	3950	180.0	468.0	3302.0	13.0	399.0	18.00	14790.0	1496.0	9.887829e+06
69	Sudan	3820	165.0	458.0	3197.0	NaN	87.0	4.00	401.0	9.0	4.373599e+07
70	Hungary	3756	491.0	1711.0	1554.0	28.0	389.0	51.00	164619.0	17037.0	9.662723e+06
71	Guatemala	3424	58.0	258.0	3108.0	5.0	192.0	3.00	31427.0	1758.0	1.787980e+07
72	Guinea	3275	20.0	1673.0	1582.0	24.0	250.0	2.00	14407.0	1100.0	1.309262e+07
73	Uzbekistan	3164	13.0	2565.0	586.0	4.0	95.0	0.40	460000.0	13765.0	3.341792e+07
74	Senegal	3047	35.0	1456.0	1556.0	12.0	183.0	2.00	35016.0	2097.0	1.669436e+07
75	Thailand	3042	57.0	2928.0	57.0	61.0	44.0	0.80	328073.0	4701.0	6.978258e+07
76	Tajikistan	2929	46.0	1301.0	1582.0	NaN	308.0	5.00	NaN	NaN	9.514051e+06
77	Greece	2878	171.0	1374.0	1333.0	19.0	276.0	16.00	153963.0	14765.0	1.042792e+07
78	Bulgaria	2427	130.0	840.0	1457.0	29.0	349.0	19.00	74096.0	10656.0	6.953369e+06
79	Bosnia and Herzegovina	2401	144.0	1680.0	577.0	4.0	731.0	44.00	59532.0	18135.0	3.282754e+06
80	Ivory Coast	2376	30.0	1219.0	1127.0	NaN	90.0	1.00	23444.0	891.0	2.630548e+07
81	Djibouti	2270	10.0	1064.0	1196.0	NaN	2301.0	10.00	22097.0	22400.0	9.864800e+05
82	Croatia	2244	99.0	2027.0	118.0	6.0	546.0	24.00	61482.0	14968.0	4.107668e+06
83	DRC	2141	63.0	317.0	1761.0	NaN	24.0	0.70	NaN	NaN	8.924918e+07
84	El Salvador	1983	35.0	698.0	1250.0	25.0	306.0	5.00	75146.0	11591.0	6.482911e+06
85	North Macedonia	1978	113.0	1422.0	443.0	21.0	949.0	54.00	25270.0	12129.0	2.083382e+06
86	Cuba	1941	82.0	1689.0	170.0	3.0	171.0	7.00	94060.0	8304.0	1.132729e+07
87	Gabon	1934	12.0	459.0	1463.0	10.0	871.0	5.00	9908.0	4463.0	2.219916e+06
88	Estonia	1823	64.0	1532.0	227.0	1.0	1374.0	48.00	75779.0	57129.0	1.326447e+06
89	Iceland	1804	10.0	1791.0	3.0	NaN	5290.0	29.00	58225.0	170739.0	3.410180e+05
90	Lithuania	1623	63.0	1138.0	422.0	17.0	595.0	23.00	267719.0	98219.0	2.725743e+06
91	Somalia	1594	61.0	204.0	1329.0	2.0	101.0	4.00	NaN	NaN	1.584302e+07
92	Mayotte	1587	20.0	894.0	673.0	11.0	5833.0	74.00	5200.0	19112.0	2.720840e+05
93	Slovakia	1509	28.0	1301.0	180.0	1.0	276.0	5.00	158414.0	29017.0	5.459382e+06
94	New Zealand	1504	21.0	1456.0	27.0	1.0	312.0	4.00	261315.0	54235.0	4.818226e+06
95	Slovenia	1468	107.0	1340.0	21.0	4.0	706.0	51.00	75110.0	36130.0	2.078910e+06
96	Kyrgyzstan	1433	16.0	992.0	425.0	5.0	220.0	2.00	100488.0	15430.0	6.512696e+06
97	Maldives	1371	4.0	144.0	1223.0	9.0	2541.0	7.00	11775.0	21825.0	5.395210e+05
98	Kenya	1214	51.0	383.0	780.0	1.0	23.0	1.00	59260.0	1105.0	5.364113e+07
99	Sri Lanka	1141	9.0	674.0	458.0	1.0	53.0	0.40	54834.0	2562.0	2.140425e+07
100	Venezuela	1121	10.0	262.0	849.0	2.0	39.0	0.40	804004.0	28266.0	2.844372e+07
101	Lebanon	1114	26.0	688.0	400.0	4.0	163.0	4.00	74224.0	10870.0	6.828370e+06
102	Guinea-Bissau	1114	6.0	42.0	1066.0	NaN	568.0	3.00	1500.0	764.0	1.962847e+06
103	Hong Kong	1066	4.0	1030.0	32.0	1.0	142.0	0.50	202930.0	27091.0	7.490759e+06
104	Tunisia	1051	48.0	917.0	86.0	3.0	89.0	4.00	47816.0	4050.0	1.180581e+07
105	Latvia	1047	22.0	712.0	313.0	2.0	555.0	12.00	99049.0	52459.0	1.888124e+06
106	Mali	1030	65.0	597.0	368.0	NaN	51.0	3.00	3483.0	173.0	2.018449e+07
107	Albania	998	32.0	789.0	177.0	5.0	347.0	11.00	13279.0	4614.0	2.878103e+06
108	Equatorial Guinea	960	11.0	165.0	784.0	NaN	687.0	8.00	854.0	611.0	1.397634e+06
109	Haiti	958	27.0	22.0	909.0	NaN	84.0	2.00	2718.0	239.0	1.138800e+07
110	Niger	945	61.0	783.0	101.0	NaN	39.0	3.00	5989.0	248.0	2.410319e+07
111	Cyprus	935	17.0	594.0	324.0	10.0	775.0	14.00	99733.0	82666.0	1.206464e+06
112	Costa Rica	930	10.0	620.0	300.0	3.0	183.0	2.00	23378.0	4594.0	5.089334e+06
113	Zambia	920	7.0	336.0	577.0	1.0	50.0	0.40	20011.0	1092.0	1.832563e+07
114	Paraguay	862	11.0	307.0	544.0	NaN	121.0	2.00	24812.0	3483.0	7.123379e+06
115	Burkina Faso	814	52.0	672.0	90.0	NaN	39.0	2.00	NaN	NaN	2.083853e+07
116	Uruguay	769	22.0	618.0	129.0	5.0	221.0	6.00	38146.0	10985.0	3.472528e+06
117	Andorra	762	51.0	653.0	58.0	3.0	9864.0	660.00	3750.0	48542.0	7.725300e+04
118	Georgia	730	12.0	522.0	196.0	6.0	183.0	3.00	48565.0	12172.0	3.989910e+06
119	Diamond Princess	712	13.0	651.0	48.0	4.0	NaN	NaN	NaN	NaN	0.000000e+00
120	Jordan	708	9.0	471.0	228.0	5.0	69.0	0.90	163173.0	16009.0	1.019267e+07
121	Sierra Leone	707	40.0	241.0	426.0	NaN	89.0	5.00	NaN	NaN	7.959309e+06
122	Chad	675	60.0	215.0	400.0	NaN	41.0	4.00	NaN	NaN	1.637228e+07
123	San Marino	665	42.0	266.0	357.0	1.0	19603.0	1238.00	3968.0	116967.0	3.392400e+04
124	South Sudan	655	8.0	6.0	641.0	NaN	59.0	0.70	3356.0	300.0	1.118005e+07
125	Malta	610	6.0	476.0	128.0	1.0	1382.0	14.00	60812.0	137763.0	4.414260e+05
126	CAR	604	1.0	22.0	581.0	NaN	125.0	0.20	11570.0	2400.0	4.820755e+06
127	Nepal	603	3.0	87.0	513.0	NaN	21.0	0.10	138841.0	4774.0	2.908039e+07
128	Ethiopia	582	5.0	152.0	425.0	NaN	5.0	0.04	81010.0	707.0	1.146462e+08
129	Channel Islands	558	45.0	517.0	-4.0	NaN	3212.0	259.00	10255.0	59039.0	1.736980e+05
130	Jamaica	552	9.0	211.0	332.0	1.0	186.0	3.00	10230.0	3456.0	2.959871e+06
131	Madagascar	527	2.0	142.0	383.0	6.0	19.0	0.07	5670.0	205.0	2.761131e+07
132	Tanzania	509	21.0	183.0	305.0	7.0	9.0	0.40	NaN	NaN	5.954100e+07
133	Congo	487	16.0	147.0	324.0	NaN	88.0	3.00	NaN	NaN	5.502963e+06
134	Réunion	452	1.0	411.0	40.0	2.0	505.0	1.00	17200.0	19225.0	8.946620e+05
135	Taiwan	441	7.0	414.0	20.0	NaN	19.0	0.30	70697.0	2969.0	2.381251e+07
136	Palestine	423	3.0	357.0	63.0	NaN	83.0	0.60	44876.0	8819.0	5.088300e+06
137	Togo	381	12.0	141.0	228.0	NaN	46.0	1.00	16747.0	2028.0	8.257247e+06
138	Cabo Verde	380	3.0	155.0	222.0	NaN	684.0	5.00	1307.0	2353.0	5.553600e+05
139	Isle of Man	336	24.0	303.0	9.0	2.0	3953.0	282.00	4523.0	53219.0	8.498800e+04
140	Mauritius	334	10.0	322.0	2.0	NaN	263.0	8.00	102247.0	80411.0	1.271559e+06
141	French Guiana	328	1.0	145.0	182.0	NaN	1101.0	3.00	NaN	NaN	2.978140e+05
142	Rwanda	327	NaN	237.0	90.0	NaN	25.0	NaN	58477.0	4527.0	1.291643e+07
143	Vietnam	325	NaN	267.0	58.0	2.0	3.0	NaN	275000.0	2828.0	9.724858e+07
144	Montenegro	324	9.0	315.0	0.0	NaN	516.0	14.00	10167.0	16188.0	6.280580e+05
145	Nicaragua	279	17.0	199.0	63.0	NaN	42.0	3.00	NaN	NaN	6.616331e+06
146	Liberia	265	26.0	139.0	100.0	NaN	53.0	5.00	NaN	NaN	5.044519e+06
147	Sao Tome and Principe	251	8.0	4.0	239.0	NaN	1148.0	37.00	175.0	800.0	2.187200e+05
148	Eswatini	250	2.0	156.0	92.0	NaN	216.0	2.00	4994.0	4309.0	1.158921e+06
149	Mauritania	237	6.0	15.0	216.0	NaN	51.0	1.00	2583.0	557.0	4.635933e+06
150	Yemen	222	42.0	10.0	170.0	NaN	7.0	1.00	120.0	4.0	2.975378e+07
151	Myanmar	201	6.0	122.0	73.0	NaN	4.0	0.10	18644.0	343.0	5.437276e+07
152	Uganda	198	NaN	68.0	130.0	NaN	4.0	NaN	84975.0	1865.0	4.557438e+07
153	Martinique	197	14.0	91.0	92.0	NaN	525.0	37.00	NaN	NaN	3.752930e+05
154	Mozambique	194	NaN	51.0	143.0	NaN	6.0	NaN	8463.0	272.0	3.115623e+07
155	Benin	191	3.0	82.0	106.0	NaN	16.0	0.20	27954.0	2313.0	1.208756e+07
156	Faeroe Islands	187	NaN	187.0	0.0	NaN	3829.0	NaN	9178.0	187904.0	4.884400e+04
157	Guadeloupe	161	14.0	115.0	32.0	3.0	402.0	35.00	3573.0	8930.0	4.001170e+05
158	Gibraltar	154	NaN	147.0	7.0	NaN	4571.0	NaN	6524.0	193636.0	3.369200e+04
159	Brunei	141	1.0	137.0	3.0	2.0	323.0	2.00	18411.0	42126.0	4.370470e+05
160	Mongolia	141	NaN	33.0	108.0	25.0	43.0	NaN	12407.0	3791.0	3.272661e+06
161	Guyana	135	10.0	62.0	63.0	2.0	172.0	13.00	1457.0	1853.0	7.861700e+05
162	Bermuda	133	9.0	81.0	43.0	2.0	2135.0	144.00	6362.0	102119.0	6.230000e+04
163	Cayman Islands	129	1.0	61.0	67.0	NaN	1965.0	15.00	8426.0	128363.0	6.564200e+04
164	Cambodia	124	NaN	122.0	2.0	1.0	7.0	NaN	16642.0	997.0	1.669458e+07
165	Trinidad and Tobago	116	8.0	108.0	0.0	NaN	83.0	6.00	2930.0	2094.0	1.399036e+06
166	Aruba	101	3.0	95.0	3.0	3.0	946.0	28.00	2070.0	19396.0	1.067210e+05
167	Bahamas	100	11.0	46.0	43.0	1.0	255.0	28.00	1972.0	5020.0	3.928570e+05
168	Monaco	98	4.0	90.0	4.0	2.0	2499.0	102.00	NaN	NaN	3.921400e+04
169	Barbados	92	7.0	70.0	15.0	4.0	320.0	24.00	4664.0	16232.0	2.873400e+05
170	Comoros	87	1.0	21.0	65.0	NaN	100.0	1.00	NaN	NaN	8.675730e+05
171	Syria	86	4.0	41.0	41.0	NaN	5.0	0.20	NaN	NaN	1.745340e+07
172	Malawi	83	4.0	33.0	46.0	1.0	4.0	0.20	2411.0	126.0	1.907456e+07
173	Liechtenstein	82	1.0	55.0	26.0	NaN	2151.0	26.00	900.0	23612.0	3.811700e+04
174	Sint Maarten	77	15.0	59.0	3.0	1.0	1798.0	350.00	438.0	10228.0	4.282500e+04
175	Libya	75	3.0	39.0	33.0	NaN	11.0	0.40	4351.0	634.0	6.861458e+06
176	Angola	69	4.0	18.0	47.0	NaN	2.0	0.10	10000.0	305.0	3.274862e+07
177	French Polynesia	60	NaN	60.0	0.0	NaN	214.0	NaN	3873.0	13795.0	2.807440e+05
178	Zimbabwe	56	4.0	25.0	27.0	NaN	4.0	0.30	37039.0	2496.0	1.484004e+07
179	Macao	45	NaN	45.0	0.0	NaN	69.0	NaN	NaN	NaN	6.484030e+05
180	Burundi	42	1.0	20.0	21.0	NaN	4.0	0.08	284.0	24.0	1.185030e+07
181	Saint Martin	40	3.0	33.0	4.0	1.0	1036.0	78.00	553.0	14328.0	3.859500e+04
182	Eritrea	39	NaN	39.0	0.0	NaN	11.0	NaN	NaN	NaN	3.541249e+06
183	Botswana	35	1.0	19.0	15.0	NaN	15.0	0.40	16100.0	6861.0	2.346458e+06
184	Bhutan	27	NaN	6.0	21.0	NaN	35.0	NaN	15342.0	19906.0	7.707260e+05
185	Antigua and Barbuda	25	3.0	19.0	3.0	1.0	256.0	31.00	183.0	1870.0	9.784600e+04
186	Gambia	25	1.0	13.0	11.0	NaN	10.0	0.40	1476.0	613.0	2.408973e+06
187	Timor-Leste	24	NaN	24.0	0.0	NaN	18.0	NaN	738.0	561.0	1.315727e+06
188	Grenada	22	NaN	17.0	5.0	4.0	196.0	NaN	3007.0	26736.0	1.124710e+05
189	Namibia	21	NaN	14.0	7.0	NaN	8.0	NaN	3027.0	1194.0	2.535948e+06
190	Laos	19	NaN	14.0	5.0	NaN	3.0	NaN	5487.0	755.0	7.264396e+06
191	Belize	18	2.0	16.0	0.0	NaN	45.0	5.00	1435.0	3616.0	3.968500e+05
192	St. Vincent Grenadines	18	NaN	14.0	4.0	NaN	162.0	NaN	209.0	1884.0	1.109050e+05
193	New Caledonia	18	NaN	18.0	0.0	NaN	63.0	NaN	5454.0	19122.0	2.852150e+05
194	Fiji	18	NaN	15.0	3.0	NaN	20.0	NaN	1300.0	1451.0	8.957840e+05
195	Saint Lucia	18	NaN	18.0	0.0	NaN	98.0	NaN	898.0	4893.0	1.835430e+05
196	Curaçao	17	1.0	14.0	2.0	NaN	104.0	6.00	504.0	3073.0	1.640260e+05
197	Dominica	16	NaN	16.0	0.0	NaN	222.0	NaN	433.0	6017.0	7.196800e+04
198	Saint Kitts and Nevis	15	NaN	15.0	0.0	NaN	282.0	NaN	391.0	7355.0	5.316100e+04
199	Falkland Islands	13	NaN	13.0	0.0	NaN	3749.0	NaN	445.0	128316.0	3.468000e+03
200	Turks and Caicos	12	1.0	10.0	1.0	NaN	310.0	26.00	126.0	3259.0	3.866200e+04
201	Greenland	12	NaN	11.0	1.0	NaN	211.0	NaN	1885.0	33210.0	5.676000e+04
202	Vatican City	12	NaN	2.0	10.0	NaN	14981.0	NaN	NaN	NaN	8.010000e+02
203	Seychelles	11	NaN	11.0	0.0	NaN	112.0	NaN	NaN	NaN	9.828500e+04
204	Suriname	11	1.0	9.0	1.0	NaN	19.0	2.00	488.0	833.0	5.860920e+05
205	Montserrat	11	1.0	10.0	0.0	NaN	2204.0	200.00	36.0	7212.0	4.992000e+03
206	Western Sahara	9	NaN	6.0	3.0	NaN	15.0	NaN	NaN	NaN	5.957040e+05
207	MS Zaandam	9	2.0	NaN	7.0	NaN	NaN	NaN	NaN	NaN	0.000000e+00
208	British Virgin Islands	8	1.0	6.0	1.0	NaN	265.0	33.00	167.0	5528.0	3.021100e+04
209	Papua New Guinea	8	NaN	8.0	0.0	NaN	0.9	NaN	2402.0	269.0	8.928690e+06
210	Caribbean Netherlands	6	NaN	6.0	0.0	NaN	229.0	NaN	424.0	16184.0	2.619800e+04
211	St. Barth	6	NaN	6.0	0.0	NaN	608.0	NaN	137.0	13875.0	9.874000e+03
212	Anguilla	3	NaN	3.0	0.0	NaN	200.0	NaN	30.0	2001.0	1.498900e+04
213	Lesotho	2	NaN	NaN	2.0	NaN	0.9	NaN	283.0	132.0	2.140514e+06
214	Saint Pierre Miquelon	1	NaN	1.0	0.0	NaN	173.0	NaN	NaN	NaN	5.797000e+03

	Week
99	19
88	18
91	18
87	17
111	21
67	15
114	21
75	16
97	19
98	19
66	14
79	16
93	18
84	17
105	20
81	17
80	16
92	18
70	15
90	18
112	21
78	16
115	21
102	20
106	20
113	21
71	15
89	18
94	18
95	19
77	16
76	16
104	20
86	17
107	20
103	20
63	14
69	15
74	16
65	14
108	20
68	15
83	17
64	14
72	15
82	17
62	14
109	21

	Week
99	19
88	18
91	18
87	17
111	21
67	15
114	21
75	16
97	19
98	19
66	14
79	16
93	18
84	17
105	20
81	17
80	16
92	18
70	15
90	18
112	21
78	16
115	21
102	20
106	20
113	21
71	15
89	18
94	18
95	19
77	16
76	16
104	20
86	17
107	20
103	20
63	14
69	15
74	16
65	14
108	20
68	15
83	17
64	14
72	15
82	17
62	14
109	21